Social Capital on Facebook

SOCIAL CAPITAL ON FACEBOOK: BONDING OR

BRIDGING RELATIONSHIPS BETWEEN INDIVIDUALS?

A PRELIMINARY STUDY IN INDONESIA

THESIS

RESEARCH PROJECT

By

Mohit Kanayolal

(1301027132)

08THE

BINUS INTERNATIONAL

BINUS UNIVERSITY

JAKARTA

2013

i

SOCIAL CAPITAL ON FACEBOOK: BONDING OR

BRIDGING RELATIONSHIPS BETWEEN INDIVIDUALS?


THESIS

Proposed as a requirement for obtaining

Sarjana Degree at

Program Information Systems

Education Level Strata-1 (Sarjana/Bachelor)

By

Mohit Kanayolal 1301027132

BINUS INTERNATIONAL

BINUS UNIVERSITY

JAKARTA

ii

2013 SOCIAL CAPITAL ON FACEBOOK: BONDING OR BRIDGING RELATIONSHIPS BETWEEN INDIVIDUALS?

A PRELIMINARY STUDY IN INDONESIATHESIS

Prepared by:

Mohit Kanayolal

1301027132

Approved by:

Supervisor

Minsani Mariani, MBA

Lecturer code: L 1258

BINUS INTERNATIONAL

BINUS UNIVERSITY

JAKARTA

2013

iii

BINUS INTERNATIONALBINUS UNIVERSITY

Major: Information SystemSarjana Komputer Thesis

Semester Odd year 2013/2014

SOCIAL CAPITAL ON FACEBOOK: BONDING OR BRIDGING RELATIONSHIPS BETWEEN INDIVIDUALS?


Mohit Kanayolal 1301027132

AbstractObjectives

To find out whether an individual’s intensity of Facebook use play a role in affecting the individual’s perceived social capital and to see whether the individual’s psychological well-being play a role in affecting the type or level of social capital affected.

Method

The research is done quantitatively and the data collection method used is questionnaires. Specifically, the statistical analysis used on the data collected is frequencies, simple linear regression as well as correlation.

Results

The research showed that the intensity of an individual’s Facebook use affects both bridging and bonding social capital although statistically it shows that bridging social capital is more affected. The research also proved that psychological well-being of an individual play a role in affecting the type and level of social capital affected.

Conclusion

Intensity of Facebook use positively and significantly affects an individual’s perceived Bridging and Bonding Social Capital. Also, psychological factors such as life satisfaction and self-esteem used to measure the individual’s psychological well-being significantly affects the type and level of social capital affected through the use of Facebook.

Key Words

Social capital, Social capital on Facebook, Bridging social capital, Bonding Social Capital

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ACKNOWLEDGEMENT

Firstly, the author would like to say thank you for the blessings of Almighty God - Who

has given him the strength, believe, courage and power to complete this research.

The author would also like to express his utmost gratitude for several individuals who

have helped him through moral, technical, and all other forms of support to ensure the

completion of this thesis. These individuals consist of:

The author’s beloved parents, Mr. Madan Khiani & Mrs. Roshni Khiani, for

their constant support, love, prayer and motivation for finishing this research.

You both mean everything to me.

Author’s sister, Ekta Khiani for the support and assistance throughout the

process of writing this research.

Author’s girlfriend, Samriti Saluja for the constant motivation, love and

understanding.

Miss Minsani Mariani, for her guidance and supervision towards the completion

of this research

The members of the panel of judges, Ms Nathalia Devina Widjaja, MBusSys,

MPA as well as Mr. Mathias Dharmawirya, B.Eng (Hons), M.Sc., for the

valuable inputs and suggestions.

Author’s cousins/extended family and relatives for their never-ending support.

Author’s close friends; Dinesh Punjabi, Luv Khoobchandani, Aakash Jaswani,

Lakesh Buxani, Chirag Buxani, Priti Samtani, Vinita Mulani, Kirty Buxani,

Ravina Alimchandani, Manisha Ramchandani, Tanira Kukreja, Divya

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Topandasani, Chirag Pridhnani, and Gita Sangtani for the companion, laughter

and valuable friendship.

Author’s teachers that have taught him a lot throughout high school.

Author’s high school friends for the memorable and crazy moments.

IS 2013 classmates for the friendship and incredible journey over the past 4

years.

All Binus International University lecturers who has taught and guided the

author at one point or another in the times of his study in Binus International.

Binus International Student Committee for the experience, laughter and amazing

journey together.

Binus International University staff including SAR, ISS, Security Personnel’s,

Student Service staff, Library Staff, Academic and Marketing department as

well as all other departments of Binus International.

Fellow respondents who has spared their time to completing the questions.

All other individual who has helped the author in any possible way.

Table of Contents

vi

CHAPTER I......................................................................................................................1

INTRODUCTION.............................................................................................................1

1.1 Background..............................................................................................................1

1.2 Problem Definition..................................................................................................5

1.3 Scope & Limitation..................................................................................................5

1.4 Aims & Benefits......................................................................................................6

1.5 Structures.................................................................................................................7

CHAPTER II...................................................................................................................11

THEORETICAL FOUNDATION..................................................................................11

2.1 Information Technology Theories.........................................................................11

2.1.1 Internet............................................................................................................11

2.1.1.1 Internet as Communication Tool..............................................................12

2.1.1.2 Effects of Internet on Social Capital........................................................13

2.1.2 Computer mediated Communication..............................................................14

2.1.2.1 Computer Mediated Communication on Social Capital...........................15

2.1.3 Social Networking Website............................................................................16

2.1.3.1 Social Networking Website as a Communication Tool...........................18

2.1.4 Facebook.........................................................................................................21

2.1.4.1 Facebook as a communication tool..........................................................23

2.1.4.2 Social Capital on Facebook......................................................................24

2.2 Social Capital Theories..........................................................................................27

2.2.1 Bonding & Bridging Social Capital................................................................27

2.3 Research Theories..................................................................................................29

2.3.1 Data Collection...............................................................................................29

2.3.1.1 Questionnaire............................................................................................29

2.3.2 Data Analysis..................................................................................................32

2.3.2.1 Frequencies...............................................................................................32

2.3.2.2 Reliability Test.........................................................................................33

2.3.2.3 Validity Test.............................................................................................33

2.3.2.4 Inferential Statistics..................................................................................34

2.3.2.4.1 Regression.................................................................................................34

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2.3.2.4.2 R-Square & ANOVA Analysis.............................................................36

CHAPTER III..................................................................................................................37

RESEARCH METHODOLOGY....................................................................................37

3.1 Research Objectives...............................................................................................37

3.2 Research Methodology..........................................................................................38

3.3 Research Question.................................................................................................41

3.3 Research Model & Hypothesis..............................................................................42

3.4 Scope.....................................................................................................................45

3.5 Data Collection......................................................................................................46

3.5.1 Questionnaire Design......................................................................................46

3.5.2 Sample Likert Scale Questions.......................................................................47

3.6 Sampling Design....................................................................................................47

3.7 Data Analysis.........................................................................................................48

3.7.1 Validity...........................................................................................................48

3.7.2 Reliability........................................................................................................48

3.7.3 Frequencies.....................................................................................................49

3.7.4 Regression......................................................................................................49

3.7.5 Correlation......................................................................................................49

CHAPTER IV.................................................................................................................50

RESULTS & ANALYSIS...............................................................................................50

4.1 Demographic Frequencies.....................................................................................51

4.1.1 Gender Frequency of Respondents.................................................................51

4.1.2 Age Frequency of Respondents......................................................................52

4.1.3 Last Education Frequency of Respondents.....................................................53

4.1.4 Current Occupation Frequency of Respondents.............................................54

4.1.5 Daily Internet Usage Frequency of Respondents............................................55

4.2 Reliability & Validity Test....................................................................................56

4.2.1 Reliability Test................................................................................................56

4.2.1.1 Intensity....................................................................................................56

4.2.1.2 Self Esteem...............................................................................................57

4.2.1.3 Life Satisfaction.......................................................................................57

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4.2.1.4 Bridging Social capital.............................................................................58

4.2.1.5 Bonding Social Capital.............................................................................59

4.2.2 Validity Test....................................................................................................60

4.2.2.1 Intensity........................................................................................................60

4.2.2.2 Self Esteem..................................................................................................60

4.2.2.3 Life Satisfaction...........................................................................................61

4.2.2.4 Bridging Social capital.................................................................................62

4.2.2.5 Bonding Social Capital................................................................................62

4.4 Hypothesis Testing................................................................................................63

4.4.1 Simple Linear Regression...............................................................................63

4.4.2 Moderated Regression Analysis......................................................................66

4.4.3 Correlations.....................................................................................................72

4.4.3.1 Correlation between Intensity and Bonding Social Capital.....................72

4.4.3.2 Correlation between Intensity and Bridging Social Capital.....................72

4.4.4 R2 (Coefficient of Determination) & ANOVA (Analysis of Variance) Analysis....................................................................................................................73

CHAPTER V...................................................................................................................80

DISCUSSION.................................................................................................................80

5.1 Discussion..............................................................................................................80

5.2 Additional Information..........................................................................................88

CHAPTER VI.................................................................................................................93

CONCLUSION & RECOMMENDATION....................................................................93

6.1 Conclusion.............................................................................................................93

6.2 Limitation..............................................................................................................95

6.3 Future Research Recommendations......................................................................96

Bibliography....................................................................................................................97

Appendix.......................................................................................................................101

Appendix 1 - Questionnaire.......................................................................................101

Appendix 2 - Journal.................................................................................................106

Appendix 3 – SPSS Results.......................................................................................146

DEMOGRAPHIC FREQUENCIES......................................................................146

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MEASURES OF FACEBOOK USAGE TO MEET NEW PEOPLE & CONNECT WITH EXISTING OFFLINE................................................................................151

VALIDITY TEST RESULT..................................................................................156

RELIABILITY TEST............................................................................................159

REGRESSION.......................................................................................................164

CORRELATION...................................................................................................170

Appendix 4 – CV.......................................................................................................171

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List of Figures

Figure 1. 1 - List of Continents on Facebook....................................................................2

Figure 1. 2 - List of Countries on Facebook......................................................................3

Figure 1. 3 - Statistics of Facebook use in Indonesia........................................................4

Figure 1. 4 - List of Cities on Facebook............................................................................3

Figure 2. 1 - Facebook Homepage..................................................................................21

Figure 3. 1 - Model / Framework Used in Original Study..............................................39

Figure 3. 2 - Model / Framework used in this Research.................................................42

Figure 4. 1 - Gender Frequency of Respondents.............................................................51

Figure 4. 2 - Age Frequency of Respondents..................................................................52

Figure 4. 3 - Last Education Frequency of Respondents................................................53

Figure 4. 4 - Current Occupation Frequency of Respondents.........................................54

Figure 4. 5 - Daily Internet Usage Frequency of Respondents.......................................55

Figure 4. 6 - Submodel Hypothesis 1..............................................................................63

Figure 4. 7 - Submodel Hypothesis 2..............................................................................64

Figure 4. 8 - Submodel Hypothesis 3a............................................................................66

Figure 4. 9 - Submodel Hypothesis 3b............................................................................67

Figure 4. 10 - Submodel Hypothesis 4a..........................................................................69

Figure 4. 11 - Submodel Hypothesis 4b..........................................................................70

Figure 5. 1 - I have used Facebook to check out someone I met socially.......................88

Figure 5. 2 - I use Facebook to learn more about other people in my class / workplace 89

Figure 5. 3 - I use Facebook to learn more about other people living near me...............90

Figure 5. 4 - I use Facebook to keep in touch with my old friends.................................91

Figure 5. 5 - I use Facebook to meet new people............................................................92

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List of Tables

Table 4. 1 - Gender Frequency of Respondents..............................................................51

Table 4. 2 - Age Frequency of Respondents...................................................................52

Table 4. 3 - Last Education Frequency of Respondents..................................................53

Table 4. 4 - Current Occupation Frequency of Respondents..........................................54

Table 4. 5 - Daily Internet Usage Frequency of Respondents.........................................55

Table 4. 6 - Reliability Test (Case Processing Summary - Intensity).............................56

Table 4. 7 - Cronbach's Alpha (Intensity).......................................................................56

Table 4. 8 - Reliability Test (Case Processing Summary - Self-Esteem)........................57

Table 4. 9 - Cronbach's Alpha (Self-Esteem)..................................................................57

Table 4. 10 - Reliability Test (Case Processing Summary - Life Satisfaction)...............57

Table 4. 11 - Cronbach's Alpha (Life Satisfaction).........................................................58

Table 4. 12 - Reliability Test (Case Processing Summary - Bridging Social Capital). . .58

Table 4. 13 - Cronbach's Alpha (Bridging Social Capital).............................................58

Table 4. 14 - Reliability Test (Case Processing Summary - Bonding Social Capital)....59

Table 4. 15 - Cronbach's Alpha (Bonding Social Capital)..............................................59

Table 4. 16 - Validity Test (Intensity).............................................................................60

Table 4. 17 - Validity Test (Self-Esteem).......................................................................60

Table 4. 18 - Validity Test (Life Satisfaction)................................................................61

Table 4. 19 - Validity Test (Bridging Social Capital).....................................................62

Table 4. 20 - Validity Test (Bonding Social Capital)......................................................63

Table 4. 21- Hypothesis 1 Variables...............................................................................63

Table 4. 22 - Hypothesis 1 Regression............................................................................63

Table 4. 23 - Table 4. 22 - Hypothesis 1 Regression......................................................64

Table 4. 24 - Hypothesis 2 Regression............................................................................65

Table 4. 25- Hypothesis 3a Variables.............................................................................66

Table 4. 26 - Hypothesis 3a Regression..........................................................................66

Table 4. 27 - Hypothesis 3b Variables............................................................................67

Table 4. 28 - Hypothesis 3b Regression..........................................................................68

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Table 4. 29 - Hypothesis 4a Variables............................................................................69

Table 4. 30 - Hypothesis 4a Regression..........................................................................69

Table 4. 31 - Hypothesis 4b Variables............................................................................70

Table 4. 32 - Hypothesis 4b Regression..........................................................................71

Table 4. 33 - Hypothesis 1 Correlation...........................................................................72

Table 4. 34 - Hypothesis 2 Correlation...........................................................................72

Table 4. 35 - R-Square Analysis Hypothesis..................................................................74

Table 4. 36 - ANOVA Analysis Hypothesis 1................................................................74

Table 4. 37 - R-Square Analysis Hypothesis 2...............................................................75


Table 4. 39 - R-Square Analysis Hypothesis 3a..............................................................76


Table 4. 41 - R-Square Analysis Hypothesis 3b.............................................................77

Table 4. 42 - ANOVA Analysis Hypothesis 3b..............................................................77

Table 4. 43 - R-Square Analysis Hypothesis 4a..............................................................78

Table 4. 44 - ANOVA Analysis Hypothesis 4a..............................................................78

Table 4. 45 - R-Square Analysis Hypothesis 4b.............................................................79

Table 4. 46 - ANOVA Analysis Hypothesis 4b..............................................................79

Table 5. 1 - Summary of SPSS Analysis.........................................................................81

Table 5. 2 - Summary of Hypothesis Result 2................................................................82

Table 5. 3 - Summary of Hypothesis Result 3................................................................85

Table 5. 4 - I have used Facebook to check out someone I met socially........................88

Table 5. 5 - I use Facebook to learn more about other people in my class / workplace. 89

Table 5. 6 - I use Facebook to learn more about other people living near me................90

Table 5. 7 - I use Facebook to keep in touch with my old friends..................................91

Table 5. 8 - I use Facebook to meet new people.............................................................92

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CHAPTER I

INTRODUCTION1.1 Background

Social networking sites have changed the way people communicate all around

the world. It has made it easier for people to maintain ongoing relationships with

friends, family, colleagues, etc. As well as create new relationships with people

in the same community or even a total stranger who lives half the world away.

Theoretically, Social network sites (SNSs) can be defined as “a web-based

services that allow individuals to (1) construct a public or semi-public profile

within a bounded system, (2) articulate a list of other users with whom they

share a connection, and (3) view and traverse their list of connections and those

made by others within the system” (Boyd & Ellison, Social Network Sites:

Definition, History, and Scholarship, 2007). Social networking sites or SNS has

been the way for people around the world to meet new people or get to know

more about people that they have met offline. The first SNS was launched in

1997 and currently there are hundreds of SNSs across the globe, supporting a

spectrum of practices, interests and users (Boyd & Ellison, Social Network

Sites: Definition, History, and Scholarship, 2007). From all the social

networking sites available, there are only a few that has attracted quite a number

of people around the world. There is one social networking site in particular that

1

has gained an enormous level of popularity over the past few years and is

currently used by over a hundred million users around the world, Facebook.

Facebook is a social networking website or service launched in February 2004.

It was owned and operated by Facebook, Inc. and was founded by Mark

Zuckerberg with his college roommates who were also Harvard

University students Eduardo Saverin, Andrew McCollum, Dustin

Moskovitz and Chris Hughes. The website initially only catered to Harvard

students which was agreed upon by the founders, but it was expanded to

gradually most universities in Canada and the United States, corporations, and by

September 2006, the website was open to everyone of age 13 and older with a

valid email address (Wikipedia Corporation, 2013).

Below is the latest statistics of the distribution of Facebook users provided by

Socialbakers.com:

Figure 1. 1 - List of Continents on Facebook

Source : http://www.socialbakers.com/countries/continents/

2

http://www.socialbakers.com/countries/continents/

Figure 1. 2 - List of Countries on FacebookSource:http://www.socialbakers.com/facebook-statistics/?interval=last-

week#chart-intervals

From the statistics provided above, it is clear that Asia is at the top of the list of

‘Continents on Facebook’ with over 260 million users. This is a very big number

considering only 6.61% of Asia’s population uses Facebook. Also, as previously

stated, Indonesia is currently on 4th position in the list of countries with the

highest number of Facebook users.

Figure 1. 3 - List of Cities on FacebookSource: http://www.socialbakers.com/facebook-statistics/cities/

3

http://www.socialbakers.com/facebook-statistics/cities/

http://www.socialbakers.com/facebook-statistics/?interval=last-week#chart-intervals

http://www.socialbakers.com/facebook-statistics/?interval=last-week#chart-intervals

Jakarta is currently the city with the 2nd highest Facebook users in the world with

Bangkok on top of the list followed by London on the 3 rd position and Mumbai

and Seoul placed on the 4th and 5th position respectively.

Figure above shows that

even with just below 20% of

Indonesia’s population uses

Facebook; it is still able to

reach just a little over 47

million users.

Figure 1. 4 - Statistics of Facebook use in Indonesia

Source: http://www.checkfacebook.com/

With the facts, figures, and examples provided above; it is clear that Facebook

has affected the lives of a lot of people in Indonesia esp. Jakarta; as well as

people around the world in many different aspects. One of the biggest aspects

that have been affected by Facebook is how people maintain their social capital.

4

http://www.checkfacebook.com/

Social Capital is a broad term and can be defined in many ways which will be

further explained in the next chapter of this research. In short, social capital can

be defined as “the actual or potential resources which are linked to a durable

network of more or less institutionalized relationships of mutual acquaintance or

recognition” (Bourdieu, 1985). It is the benefit derived from one's position in a

social network, the number and character of the ties one maintains, and the

resources those ties themselves possess (Wellman & Wortley, 1990). There are

2 types of social capital; bonding and bridging which will also be further

explained later in this chapter as well in the next chapter.

1.2 Problem Definition

The primary objective of this research is to establish which type of social

capital, bonding or bridging, is this computer mediated communication (CMC)

through Facebook; is able to enhance or supplement. In other words this

research is conducted to find out what kind of social capital will an individual be

able to build through Facebook; will they be more able to bond their stronger

ties or bridge their weaker ties through this particular social networking

phenomenon; Facebook.

1.3 Scope & Limitation

In this research, the researcher will focus on the social capital aspect of

Facebook in Indonesia and how Facebook has affected the way people socialize.

5

This research will establish which type of social capital can be built through

Facebook.

As a unit of analysis, this research will only be targeted towards Facebook users

in Indonesia. Having said this, in order to conduct this research, information will

be gathered by giving out questionnaires which are carefully planned and

designed to Facebook users who reside in Indonesia. The data collected from

these questionnaires will be deeply analyzed in order to produce useful

information. The information produced from the analyzing process will enable

the researcher to draw a conclusion at the end of this research. The questionnaire

developed by the researcher will be given out to 200 Facebook users. The

researcher decided to only give out 200 questionnaires due to the limited time

available to conduct this study.

1.4 Aims & Benefits

The aims of writing this thesis are:

To aid future researchers in knowing which type of social capital relationship

(bonding or bridging) can be affected through Facebook.

To measure the impact of Facebook towards bonding and bridging social capital

relationships.

The benefits of writing this thesis are:

Provide useful data that will be useful for future reference regarding the impact

of Facebook towards an individual.

6

This research will benefit any other researcher who would like the knowledge

regarding this topic or even conduct further research due to the limitations of

this research.

This research will also benefit anyone who would like to maintain a healthy

social capital; using this research, they will know who they will be able to reach

and maintain stable relationship with through Facebook and who they have to

maintain face-to-face (F2F) relationship with.

This research might also be usable for people who would like to promote

themselves through Facebook; using this research they will be able to learn who

will respond positively to them and who won’t.

To complete my credits at Binus University and graduate. This research or thesis

is the last mandatory course I have to complete before being able to graduate

from Binus International University after 4 years of studying here.

1.5 Structures

Chapter 1 – Introduction

This chapter discusses the general idea of this thesis. This chapter covers:

The background of the research.

Problem definition.

The scope & Limitation.

Aim & benefits of this research.

The structure of the thesis.

7

Chapter 2 – Theoretical Foundation / Literature Review

This chapter will explain all the theories and frameworks or models which

are going to be used to support the design of solution for the problem.

The summarized version of the relevant theories will be

comprehensively presented. These supporting theories can be referenced

from the researches that have been conducted in the field of this research

or from textbook and a number of other sources.

Based on the relevant theories discussed in the previous section of this

chapter, a model or formula which presents the relationships between the

different variables will be developed. This model or formula will provide

a way to find the solution to the problem which was defined in the

previous chapter.

Chapter 3 – Research Methodology

In this chapter, the researcher will elaborate the focus of this research

further; this chapter will present:

Research Objective

o Presenting the research question(s)

o Hypotheses

o Research scope or boundaries

8

o Research design

o Data collection method

o Sampling plan

Data analysis method

Chapter 4 – Research Findings

This chapter will present the statistical analysis performed on the data

collected in order to extract valuable information and provide possible

solution to the research problem. This chapter will then discuss the

results of the findings as well as the information that can be extracted

from it. Tables and figures will be used by the researcher in order to

explain the research result.

Chapter 5 – Discussion

This chapter of the research will discuss the results obtained from the

statistical analysis which was conducted in the previous chapter of the

research.

Chapter 6 – Conclusion & Recommendation

This last chapter of the research contains the conclusion of the overall

result of the research where the most important findings are summarized

and explained.

9

The second section of this chapter will contain suggestion and

recommendation for future researchers who wants to do research on the

same or similar topic.

This chapter will also discuss the research questions which were able to

be answered through the study as well as the limitations of the current

study.

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CHAPTER II

THEORETICAL FOUNDATION

2.1 Information Technology Theories

Here are some theories related to information technology that can be related to

the topic of this research.

2.1.1 Internet

The term internet which actually stands for inter-networking can be

defined as a global network that connects computers around the world

using a backbone network that supports interchange of vast amount of

data and information at high speed and covering long distances. The data

or information carried by the internet can be in various formats such as

e-mails, online chats or instant messages, file transfer or file sharing,

online gaming as well as hypertext documents. These data or

information which is interchanged through the internet uses one

standardized Internet Protocol Suite or usually recognized as TCP/IP.

According to Turban, Rainer & Potter (2003, p.201), the internet actually

began in the year 1969 as a network called ARPANET. When

ARPANET was first developed, its primary objective was to allow

researchers to exchange information and share computing resources

regardless of the location while at the same time creating a resilient wide

11

area network to improve communication for the military. During the

early stages of the ARPANET, very few people had access to it. Only the

military, defense contractors and universities doing research on military

and defense had access to it. By the 1980’s two more networks were

founded, they were Computer Science Network (CSNET) and BITNET.

The 3 networks mentioned above; ARPANET, CSNET & BITNET are

the foundation of the internet today.

2.1.1.1 Internet as Communication Tool

If we look at the characteristics of the internet, we are going to

find that the internet is, in many ways, similar to earlier media for

communication such as letter writing, telephone, telegraphs, etc.

“Certain capacities and uses of Internet communication uniquely

shape a user’s perceptions and interactions. These influences

extend beyond the interpersonal to the social and cultural;

outcomes of these communication processes have the potential to

shift sense- making practices at the cultural level. Essentially, the

Internet mediates– and in some ways moderates – interactions

and the possible outcomes of these interactions at the dyadic,

group, and cultural level” (MARKHAM, 2003)

12

2.1.1.2 Effects of Internet on Social Capital

There are a number of ways the internet affects social capital:

1. The internet transforms social capital – The internet has

created a cheap and convenient way of communicating with

people who share the same interest. The benefits that are

brought about by the internet may lead to a major

transformation from a local and group-based community to a

dispersed and interest-based community. This affect will

reduce the level of social contact and civic involvement

between people in a community.

2. The internet demolishes social capital – “The Internet through

its entertainment and information capabilities draws people

away from family and friends. Further, by facilitating global

communication and involvement, it reduces interest in the

local community and its politics” (Nie, Erbring, & D, 2002)

3. The internet supplements social capital – The internet may act

as an additional means of communication that people can use

to maintain existing social relationships as well as civic

engagements. The role of the internet is to provide an

additional electronic means of communication on top of face-

to-face and telephonic means of communication. The internet

13

also provides means for people to share their hobbies and

political interests. This suggests that the internet supplements

social contact and civic involvement by providing additional

means of communication which is termed as Computer

Mediated Communication or CMC (Wellman, Quan-Haase,

Witte, & Hampton, 2001)

2.1.2 Computer mediated Communication

John December from the University of Indiana (1996) defined Computer

Mediated Communication as “the process by which people create,

exchange, and perceive information using networked

telecommunications systems that facilitate encoding, transmitting, and

decoding messages” (December, Units of analysis for Internet

communication, 1996). The next year, he again defined CMC as

Computer-Mediated Communication is a process of human

communication via computers, involving people, situated in

particular contexts, engaging in processes to shape media for a variety

of purposes (December, The World Wide Web Unleashed 1997, 1997)

Computer mediated communication is; as the term suggests, a means to

communicate to other individuals from anywhere around the world using

computer as the media/medium of communication. During the early

stages of CMC, many researchers have mentioned that building

relationships with other individuals through CMC is quite impossible as

14

the media is not rich enough if compared to face-to-face communication

as it does not support intensive interactions as well as complex

informational and emotional content. In other words, CMC can only be

used for simple, straightforward types of communication (Daft, Lengel,

& Trevino, 1987). Other early CMC researchers also suggests that CMC

is not rich enough for people to build meaningful or intimate

relationships as all contextual and physical cues are filtered out (Kiesler,

J, & McGuire, 1984).

Today, after the vast growth of the internet, CMC has almost replaced all

other forms of communications. CMC is now rich enough that it may

even replace face-to-face or other conventional forms of communication.

“CMC is now an important resource for supplementing supportive

relationships, especially in cases where the people involved are

geographically separated from these traditional sources of social

support” (Wright & Webb, 2011).

2.1.2.1 Computer Mediated Communication on Social Capital

Using a simple definition, social capital can be defined as any kind of

resources that is brought about by interaction between 2 or more people.

On the other hand, computer mediated communication is now used by

people worldwide to interact with other individuals or socialize. There

are methods like online games and social networking websites which

people use to interact with a large number of people who share the same

15

interest; which in social capital are known as bridging. There are also

methods in CMC which are used to maintain close, emotional

relationships (for example instant messaging); this is also known as

bonding. These methods provided by CMC to maintain social capital

have created an illusion on their users that they are able to separate

themselves from the offline world while at the same time being able to

stay connected with other people. This has resulted in CMC users to

spend time engaging themselves in online social activities like posting

status updates or instant messaging under the illusion that these activities

provide the same value of social capital compared to offline social

capital (Ross, 2010).

2.1.3 Social Networking Website

As mentioned in the previous chapter, social networking website or SNS can be

defined as “a web-based services that allow individuals to (1) construct a public

or semi-public profile within a bounded system, (2) articulate a list of other

users with whom they share a connection, and (3) view and traverse their list of

connections and those made by others within the system” (Boyd & Ellison,

Social Network Sites: Definition, History, and Scholarship, 2007).

Social Networking Websites were introduced to the world in the year 1997 in

the form of Sixdegrees.com. Within a few years, there are numerous amount

social networking websites that were created attracting millions of people

worldwide to join and share their interest. Each social networking site has its

16

own culture, personality and uniqueness that attract more and more people to

sign up and conduct their social activities like sharing and discussing their

hobbies, interests, political views. Some social networking websites targets

diverse audiences while some websites choose to cater to people with a specific

gender, race, religion, political view, etc. The level of technology applied and

service offered also differs with each website with some providing mobile

connectivity tools, instant messaging tools, blogging tools and photo/video

sharing tools (Boyd & Ellison, Social Network Sites: Definition, History, and

Scholarship, 2007).

At first, social networking websites were not as big of a deal as it is today.

Today, social networking websites are a big deal and is a global phenomenon.

Social networking websites have gained popularity at a global scale and the

figures and statistics are not showing and decline in the level of SNS adoption

worldwide. Many people think that people use social network sites in order to

meet strangers from all over the world and communicating or ‘networking’ with

them online. Instead, what makes social network sites so unique is that they just

enable users to visualize their social networks. This visualization will then result

in creating connections that would not be made in any other way. In other

words, social network enables people who share some offline connection to

strengthen their “latent ties”. This concept of connecting people who are already

a part of a person’s extended network is the primary goal of most social network

sites (Boyd & Ellison, Social Network Sites: Definition, History, and

Scholarship, 2007).

17

2.1.3.1 Social Networking Website as a Communication Tool

Social networking sites such as Facebook, Twitter and MySpace have

now become not only a habit, but also part of people’s daily life as a way

to communicate with others. Social network sites have created a major

platform for people to maintain their offline relationships by

communicating with them online. This is also called ‘offline to online’

relationships. By doing this, people are building the online version of the

relationships they have in real life (Hans, 2009).

There are 3 ways by which people communicate through social

networking sites:

1. Directed communication with individual friends – This is where a

person communicates directly with their online friends using

facilities provided by the site for example posting on a friends

profile page, sending them a message, commenting on a friends

picture, instant messaging, photo tagging, video chat, etc. Each

social networking site creates unique mechanisms which people

use to communicate directly with a specific friend. A very good

example of such mechanism is the ‘Like’ button or the ‘Poke’

option in Facebook. All of these actions or mechanisms I have

mentioned above involve a person signaling another person

directly as a way to communicate with them. Directed

communication is designed to improve relationships between

18

individuals as well as enabling bonding and bridging of social

capital. The concept of direct communication involves one-on-

one messages which are believed to be rich and is able to

strengthen relationships. At the same time, the concept of

mutuality or interchange means there is a two way

communication which is able to provide each other with personal

information or at least some details of their daily life. The content

of this two way communication is the key to maintaining

relationships as well as making new ones (Burke, Kraut, &

Marlow, Social Capital on Facebook: Differentiating Uses and

Users, 2011).

2. Broadcasting - This is a situation where there is a one way

communication between the individual who is currently on the

social networking site and the public or in this case ‘online

friends’. This type of communication occurs when an individual

updates their profile with new information or updates their

‘status’ on Facebook or tweets about their day in Twitter.

Broadcasting can be considered an indirect way of

communicating. Although this method of communicating can be

considered less intimate or private, they might still be useful to

maintain current relationships and creating new ones. Information

extracted from one’s profile and an individual’s status updates

can reveal user’s similarities and can create conversational topics

19

(Burke, Kraut, & Marlow, Social Capital on Facebook:

Differentiating Uses and Users, 2011). Hancock and colleagues

found that college students who mined information from a

stranger’s Facebook profile were able to make that stranger like

them more, by casually referencing shared interests (Hancock,

Toma, & Fenner, 2008); (Burke, Kraut, & Marlow, Social Capital

on Facebook: Differentiating Uses and Users, 2011).

3. Passive Consumption of social news – This is quite similar to

broadcasting except this involves the person who simply reads

other people’s updates. This too is a one way communication

which can still be valuable to maintain current relationships as

well as create new ones.

20

2.1.4 Facebook

Figure 2. 1 - Facebook Homepage

Source: www.facebook.com

Facebook is without a doubt one of the most influential SNS website on the

internet. With over a billion users, it is the biggest SNS website to have ever

been created. Facebook users range from different social network based on high

school, universities, colleges, corporations and geographic areas.

Starting in 2004, Facebook already started gaining popularity later that year with

the introduction of groups and ‘wall’ posts. Facebook gained even more

popularity when they were introduced to the global public in 2005 where the

number of Facebook users immediately doubled. By the year 2007, the user

count has grown 10 times in size (Jeff Ginger, 2007). Today, Facebook has over

a billion users and is ranked as one of the most visited websites on the internet.

21

Some sources claim that Facebook currently is the 3rd most visited websites in

the world based on page views and at the same time account for 1% of all time

spent on the internet (Abram, 2007) (Freiert, 2007) (Jeff Ginger, 2007). Out of

Facebook’s 1 billion active users, 60% log in daily and some even opens

Facebook multiple times a day. Research has shown that the average visitor

spends up to 3 hours of their time on Facebook each month (Arrington, 2005).

These visitors spend their time doing different activities on Facebook.

According to Online Education Database (2007), the most common activities

based on the amount of time spent are (in ascending order): joining and

browsing networks, search for groups and other members, joining or visiting

groups, browsing pictures, interacting with applications such as online games as

well as browsing user profiles. These users come from different age groups, with

the most common age group being ‘between 12 and 24’ as well as ‘35 and up’

(Andrew Lipsman, 2007)

Since its debut, Facebook has attracted millions upon millions of users and has

spread from its initial college users, to high school users, to professionals and

even large corporations. People have also come to rely on this social networking

site to assist in many other aspects other than socializing (Nicole, Andrew,

Justin, & Laura, 2010). For example, politicians promote their campaigns

through Facebook, amateur bands or artists tries to gain popularity by posting

their work in Facebook, a person’s Facebook profile can determine whether

he/she gets the job they applied for as many large corporations treats their

Facebook profile as their ‘Online resume’. Currently, Facebook has more than

22

one billion active users (Agence France-Presse, 2012) and around 600 million of

these users access their Facebook accounts daily through their mobile devices.

Indonesia is currently sitting in 4th place in the list of top 10 countries with the

most Facebook users with 47 million active accounts (Agence France-Presse,

2012).

2.1.4.1 Facebook as a communication tool

A survey conducted in the year 2009 by Prompt Communications

showed that Facebook is the most popular communication tool followed

by SMS and e-mail. This result is not surprising considering Facebook is

the most popular social network in the world (Sachoff, 2009). With over

1 billion users, Facebook can be used as a very resourceful

communication tool. Corporations for example, can use business pages

or groups to communicate externally while at the same time they can

make messaging or instant messaging or even the newly introduced

video chat as a tool to communicate internally with other staff members

or even managers or subordinates. High schools, colleges, universities

can use their pages to pass on important messages to students or

teachers/lecturers. Facebook can be used as a communication tool in a

million different ways. The fact that it is global makes it even more

useful in certain situations like a multinational company launching their

new product and gaining popularity through Facebook.

23

Facebook has become the first alternative to phone calls. When a person

is trying to pass on a message to another person, Facebook is the second

alternative after calling. The fact that Facebook came before SMS or

texting and e-mail is a major sign that Facebook’s reach is strong enough

to replace conventional texting as well as e-mail.

2.1.4.2 Social Capital on Facebook

Before Facebook, people use their ‘online profiles’ in social networking

sites such as Friendster or MySpace simply to get updated about the

people they are connected to in their ‘online profiles’. People barely

spend more than two hours a week to update their ‘online profiles’ and to

see what others have updated on their profiles. People maintain healthy

social capital by meeting with friends; family and colleagues while at the

same time meet new people at random situations. Then Facebook came

into the picture and changed everything. Facebook changed the concept

and definition of social networking site as a whole. Social networking

sites turned from just another pastime to part of a person’s daily life.

Online profiles turned from a mere virtual account to an online

representation of a person and his/her life. People started to care more

about their Facebook profiles or online profiles and socializing through

Facebook compared to maintaining healthy offline relationships.

Facebook has provided an alternative and easier way for people to

maintain their relationships or in this case ‘online relationship’. It is

easier and much more efficient because a person can communicate with

24

their ‘Friends’ on Facebook with a few simple clicks of a button and at

the same time opens up the possibility of communicating with friends,

family members or even a complete stranger who can be located

anywhere in the world with only a few simple steps. In other words,

anyone can now maintain their social capital through Facebook. Many

people are now primarily communicating with other people through

Facebook compared to the rather conventional ways such as face-to-face

or over the phone. This method of maintaining relationships and/or an

individual’s social capital through Facebook can be considered

unconventional and is ought to be accepted in different ways by different

groups of people. As mentioned earlier in this chapter, there are 2 types

of social capital which also concerns the different groups of people

affected by Facebook. “Researchers typically distinguish between two

forms of social capital: bonding social capital, which is derived from

one’s closest relationships and takes the form of emotional and tangible

support such as “big favors”; and bridging social capital, which is

associated with weaker ties and access to novel or non-redundant

information, such as job leads” (Putnam R. D., 2000).

Studies have been conducted by researchers all over the world to

measure the effect of social networking sites on social capital. Burke,

Marlow & Lento drew a conclusion that intensive Facebook usage is

somehow related to bonding social capital but at the same time there is

an uncertain relationship when it comes to bridging social capital. They

25

also stated that the level of loneliness of active Facebook users can be

reduced through bonding social capital (Burke, Marlow, & Lento, Social

network activity and social well-being, 2010).

In the year 2008, Steinfeld and few other researchers investigated the

relationship between Facebook use, level of psychological well-being

and bridging social capital. Through their research, they found that self-

esteem is a moderating factor between Facebook use and bridging social

capital. At the end of their research, they were able to conclude that

people with lower self-esteem were able to benefit more through

Facebook usage in terms of bridging social capital (Ertan, 2011).

Furthermore, in the year 2009 Valenzuela et al. discovered that there is a

positive association between intensity of Facebook use and life

satisfaction as well as social trust. It is pretty clear that life satisfaction

and social trust have a causal relationship but there is some uncertainty

regarding the direction of the relation itself. It was argued that people

who belong to trusted networks tend to have higher life satisfaction

while it was also suggested that people with a higher life satisfaction is

more able to build trusted network (Ertan, 2011). In addition;

Valkenburg, Peter & Schouten (2006) concluded from their research that

the use of social network sites may be an effective way of enhancing

self-esteem for young adolescents in order to improve their academic

performance (Valkenburg, Peter, & Schouten, 2006). This concept is

now well known as social network scholars. Besides improving

26

academic performance, a person’s improved social capital resulting from

the use of social networking site is essential for subjective well-being

and physical health (Helliwell & Putnam, 2004).

All the studies and researches mentioned above have proven that there is

a degree of social capital involved in Facebook as well as other social

networking sites along with the benefits.

2.2 Social Capital Theories

“The concept of social capital traces its roots to the work of Bourdieu (1986)

and Coleman (1988), with subsequent extension by Burt (1992), Putnam (1995),

and Lin (2001). Social capital can be considered as ‘the aggregate of the actual

or potential resources which are linked to possession of a durable network of

more or less institutionalized relationships of mutual acquaintance and

recognition’ (Bourdieu, 1986: 248). Social capital can be understood as a form

of capital, like financial or human capital, that is embedded in the relationships

between individuals, and can be measured at the individual or group level”

(Ellison, Steinfeld, & Lampe, 2011).

2.2.1 Bonding & Bridging Social Capital

Putnam (2000) delineated two basic forms of social capital: bonding and

bridging. Bonding social capital describes benefits from close personal

relationships, which might include emotional support, physical succor, or

other ‘large’ benefits (such as willingness to loan a substantial sum of

27

money). Bridging social capital, the benefits derived from casual

acquaintances and connections, can also lead to tangible outcomes such

as novel information from distant connections and broader world-views

(Putnam R. , 1995). Empirical research confirms the practical importance

of bridging social capital. In Granovetter’s (1973) work on ‘the strength

of weak ties’, weak ties in a social network were more likely to have

information not possessed by the individual or by the individual’s strong

ties (Granovetter, 1973). Similarly, Boase et al. (2006) found that those

with a wider range of occupations represented in their social circle were

more likely to get help doing things like changing jobs or finding health

information (Boase J, 2006) (Ellison, Steinfeld, & Lampe, 2011).

“There are several different forms of social capital. It can be a tie among

family members, with neighbors, ties from shared experience, cultural

norms, common purposes and pursuits. Social capital can have a group

base, a network base or an institutional base. An extended family

network, a clan, a tribe, a farmers’ group, community-based groups in a

traditional sense; and a book club, a youth club, NGOs, internet forums,

social networking sites, in the modern sense. Membership in a political

party or even citizenship of a state can qualify as a social capital.”

(Panth, 2010) Robert D Putnam stated in his book, Bowling

Alone classified social capital into two distinct types, which he termed as

bonding vs. bridging in social capital (Panth, 2010) (Putnam R. , 1995)

(Putnam R. D., 2000).

28

http://www.bowlingalone.com/

http://www.bowlingalone.com/

2.3 Research Theories

Below are the theories or methods that are going to be used in order to provide a

solution to the given problem.

2.3.1 Data Collection

Data collection can be considered the second step of the research process after

problem recognition. This data collection process can be done by giving out

questionnaires and/or conducting interviews. As this research will involve

giving out questionnaires, the theories related to data collection through

questionnaires will be explained in this next section.

2.3.1.1 Questionnaire

Questionnaire is one of the most commonly used data collection

methods. Questionnaire can be defined as a preset group of questions

which will be given out to specific/random respondents in order to

provide information needed to produce a solution.

Sekaran (2003 p.238) stated that there are several guidelines in order to

create good questionnaires:

Principles of wording – This highlights issues such as:

o Content & purpose – Only questions that have a clear

purpose and objective should be included in the

questionnaire. Unnecessary questions should be avoided.

The kind of questions included should follow the nature

of the variable (subjective or objective)

29

o Language & wording – The researcher must use the right

words and proper language that can be easily understood

by the respondents. The researcher must make sure that

the words/language used does not confuse the respondent

as it may lead to incorrect results.

o Type & form of questions – The type and form of each

question must be carefully decided by the researcher. The

different types/forms are:

Open-ended/close-ended questions – Open-ended

questions allow the respondents to answer in any

way they choose while close-ended questions only

allow the respondents to choose among a set of

answers given by the researcher.

Positively worded / negatively worded – Both

must be used to make sure respondents who are

not interested in completing the questionnaires

stay conscious.

There are also certain types of questions that must

be avoided:

Ambiguous Questions – Questions that are

hard to understand

Double-barreled questions – Questions

containing subparts with different answers

30

Recall-dependent questions – Question

where respondents must recall past

experiences

Leading questions – Questions that lead

the respondents to respond in a specific

manner

Loaded questions – Questions with

strongly disturbing phrases

Social desirability

Long questions with more than 20 words

o Sequence of questions – The researcher must make sure

the questions are in sequence so the respondents can

answer the questionnaire with ease from beginning to end.

The most common approach is called the funnel

approach. This is where the questions are sequenced from

general questions to more specific questions.

o Classification data (personal information) – Questions

that asks the respondent to input their personal

data/information such as age, gender, educational level,

marital status, income, etc. is usually put at the beginning

of the questionnaire. This information gathered is

important since it can explain/classify the respondent’s

characteristics.

31

o Measurement – The researcher must ensure that the data

collected are suitable for hypothesis testing. There are

several principles to be followed to make sure that the

questions and the data that will be collected are suitable.

These principles usually covers :

Various scaling techniques

Assessment of goodness of method(s) chosen

o General ‘getup’ – This is to make the overall appearance

of the questionnaire look more interesting and well-

organized to the respondents. This includes:

Introduction

Questions logically organized along with brief

instructions on how to answer the questions

Neatly aligned

Correct placement of demographic questions

Closing

2.3.2 Data Analysis

These are several methods of analysis which are going to be used in this study:

2.3.2.1 Frequencies

The objective of the author in using frequency distribution is to obtain a count

of the number of responses associated with different variables, usually one

variable at at time (N.K.Malhotra, 2012)

32

2.3.2.2 Reliability TestA good questionnaire’s reliability and validity has to be tested prior to

distribution so that the result which will be retrieved from the research

will be good.The tool that is used to test for reliability is Cronbach’s

Alpha, using the measure of internal consistency that the closer the alpha

is to 1, the more reliable the data is. Cronbach’s alpha reliability

coefficient normally ranges between 0 and 1. (Kanayolal, 2012)

The variables that will be tested using Cronbach’s Alpha are: Intensity,

Self-Esteem, Life Satisfaction, Bridging Social Capital & Bonding

Social Capital

A variable is said to be reliable when:

Result α 0,60 = Reliable

Result α < 0,60 = Not reliable

2.3.2.3 Validity Test

To know whether or not the indicators in the variable questions are valid

to be a measuring scale, the author has conducted a validity test by

observing the Corrected Item-Total Correlation.

Item Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total

Correlation

Cronbach's

Alpha if Item

Deleted

Corrected item-total correlations are the correlations between

scores on each item and the total scale scores. If the scale is

33

internally consistent you would expect these correlations to be

reasonably strong.

Alpha-if-item-deleted statistics show that if we removed any one

item, alpha for the remaining three would be worse than alpha for all

four items. Therefore it is worth retaining all four. If the alpha-if-

item-deleted statistics showed that removing an item would lead to

an increase in alpha, then we would consider doing that in order to

improve the internal consistency of the scale.

The variables that will be tested using Corrected Item-Total

Correlation are: Intensity, Self-Esteem, Life Satisfaction, Bridging

Social Capital & Bonding Social Capital

Testing the validity of research criteria:

Result: rcount > r table = validity requirements met.

Result: rcount <r table = validity requirements not met.

2.3.2.4 Inferential Statistics

The main aim of inferential statistics is to answer the research

questions. In this research, Simple Linear Regression and Correlation

Analysis will be conducted in order to answer the research questions.

2.3.2.4.1 Regression

Regression analysis is used to know the effect of one variable

(independent variable) towards another variable (dependent

variable). In this part, the previously developed hypothesis will be

34

tested against the data that has been gathered through questionnaire

and SPSS will be used as the main processing tool.

There are 3 different types of variables involved here i.e. independent

variable, dependent variable and moderating variable.

Independent Variable is a variable that is selected or controlled

by the researcher, to determine its relationship to the observed

outcome of the research—also called explanatory, predictor, or

manipulated variable (National Service-Learning ClearingHouse,

2013).

Dependent Variable (DV): The variable being measured as an

outcome—also called outcome, response, criterion, or explained

variable (National Service-Learning ClearingHouse, 2013).

Moderator Variable: A variable that is related to the direction or

strength of the relationship between the independent and

dependent variables (Baron & Kenny, 1986)

A simple linear regression will be used on each independent variable against

the dependent variable with or without the moderating variable (depending

on the hypothesis being tested). The result of each regression will come in 3

different tables.

The Coefficientsa Table will show the results of the regression and present

the “t” value of the variables as well as the regression coefficient (β). An

35

explanation of the values in the table will be provided along with the

decision to accept or reject the hypothesis (Ha).

2.3.2.4.2 R-Square & ANOVA Analysis

The R-Square (R2) of each regression will show how much of the variance

in the independent variable is cause by the dependent variable. R2 tells how

much the regression line approximates the real data. The closer the R2 value

is to one (1), the more useful the equation is in making predictions.

ANOVA aims to know whether or not the model that was built fits in

predicting the dependent variable.

36

CHAPTER III

RESEARCH METHODOLOGY

In this chapter, the researcher will start by explaining the objectives of this research as

well as the research questions or problem. This will then be followed by the research

model or framework and the hypothesis used to provide a solution to the given problem.

The researcher will also discuss the scope of the research, the data collection method

used, questionnaire design and data analysis methods. The purpose of this chapter is to

make readers understand the whole concept of this research as well as the research

methods used.

3.1 Research Objectives

The objective of this research is to find out:

Whether intensity of Facebook use has an impact on a person’s social

capital.

What type of social capital is more affected by the intensity of Facebook use

i.e. Bridging or Bonding Social Capital?

Whether psychological factors of an individual play a role in which type of

social capital affected through the intensity of Facebook use.

Whether psychological factors of an individual play a role in the level of the

person’s social capital affected through the intensity of Facebook use.

37

3.2 Research Methodology

Research methodology can be defined as the methods used in obtaining as well as

analyzing the data. This research can be classified as a descriptive research as this

research will describe the effects of Facebook on an individual’s social capital and Does

Facebook help in bridging or bonding their social capital. On the other hand, this

research can also be categorized as hypothesis testing since this research will study

about the correlations between user’s intensity of Facebook use, self-esteem and life

satisfaction on the bridging and bonding of their social capital. The model and

hypothesis will be discussed later in this chapter and will ease the reader’s

understanding of the research.

The journal by which the researcher based this research on is “The Benefits of

Facebook “Friends”: Social Capital and College Students’ Use of Online Social

Network Sites” by Nicole B. Ellison, Charles Steinfeld and Cliff Lampe. The researcher

and the authors of the journal shares a quite similar objective which is to measure the

effects of Facebook on an individual’s social capital while at the same time taking into

account the individuals self-esteem and life satisfaction. The reason that made the

researcher choose this journal and this topic as a whole is because he would like to find

out if Facebook; the social networking site that has literally changed the way people

socialize and communicate, is able to maintain an individual’s social capital just by

using Facebook to communicate as well as to socialize.

Although the researcher and the authors of the journal have similar objectives and

purpose, there are also a few ways where the researcher would like to conduct his

38

research differently. To begin with, the researcher has decided to modify the model

used by the authors of the journal. Below is the original model and hypothesis used in

the journal:

Figure 3. 1 - Model / Framework Used in Original Study

H1 - Intensity of Facebook use will be positively associated with individuals’

perceived bonding social capital.


perceived bridging social capital.

H3a – The relationship between intensity of Facebook use and bonding social

capital will vary depending on the degree of a person’s satisfaction with life.

39

H3b - The relationship between intensity of Facebook use and bridging social


H4a - The relationship between intensity of Facebook use and bonding social

capital will vary depending on the degree of a person’s self-esteem.




perceived maintained social capital.

The researcher have decided to use the same variables used in the journal but have

decided to make a few changes to the model as well as the hypothesis. The researcher

have decided to omit the ‘Maintained Social Capital’ from the model as well as ‘H5 -

Intensity of Facebook use will be positively associated with individuals’ perceived

maintained social capital’ from the hypothesis. The reason of this omission is because

the researcher believes that there are only 2 core values of Social capital which are

bridging and bonding. Maintained social capital refers to those relationships, and the

benefits we derive from them, that we maintain despite having shifted geography,

interests or workplaces. In the case of Facebook, they may be the relationships we

forged in high school with people who went off to different colleges (Bigelow, 2007).

In other words, maintained social capital can be defined as how Facebook can help

users recover lost bridging social capital, which would be close friends and old

classmates who have fallen out of contact over time (Bainum, 2010).

40

From the description of maintained social capital provided above, the researcher have

decided to omit maintained social capital from the model and hypothesis as the concept

of maintained social capital is just an extension of bridging social capital. Instead, the

researcher used the two core values of social capital i.e. bonding and bridging social

capital.

The model and hypothesis used in this research will be shown and discussed later in this

chapter.

3.3 Research Question

This purpose of this research is to answer the following questions:

Research Question 1

Does the level of intensity of an Individual’s Facebook use affect his/her

perceived social capital?

Research Question 2

What type of an individual’s social capital (bridging or bonding) is

affected by using Facebook to communicate and socialize?

Research Question 3

Does the intensity of Facebook use have a positive impact on an

individual’s perceived bridging social capital?

Research Question 4

Does the intensity of Facebook us have a positive impact on an

individual’s perceived bonding social capital?

41

Research Question 5

Is an individual’s life satisfaction and self-esteem a factor in the level of

social capital (bridging or bonding) affected through the intensity of

his/her Facebook use?

3.3 Research Model & Hypothesis

Figure 3. 2 - Model / Framework used in this Research





H3a – The relationship between intensity of Facebook use and bonding social


42









o According to previous studies done regarding social capital on the

internet especially in social networking sites, internet based-linkages is

important for the formation of weak ties which also serves as the basis of

bridging social capital as these kind of relationships can be supported

through the use of internet or social networking sites due to the search

capabilities and communication facilities provided (Resnick, 2001).

Social networking site is a very easy, efficient and cheap method to

maintain or even increase the weak ties that an individual could form

(Boyd & Donath, Public Displays of Connection, 2004). Based on the

previous studies conducted, I propose the first hypothesis.



43

o There is quite an uncertainty when it comes to the relationship between

Facebook use and the increase in an individual’s bonding social capital.

Williams (2006) pointed out that there has been little research conducted

that clearly examines the effect of the Internet on bonding social capital

(Williams, 2006). Researchers have studied and proved that increase in

internet use will somehow diminish an individual’s social capital due to

the reduction in offline communication but at the same time there has

been not studies or researches done that sufficiently explores the gains

that one might benefit from it (Williams, 2006). Thus, this second

hypothesis is proposed to test the relationship between Facebook and

bonding social capital.

H3a – The relationship between intensity of Facebook use and bridging social






H4b - The relationship between intensity of Facebook use and bonding social


o The internet and social networking sites have proven to open up new

possibilities for people with low self-esteem and life satisfaction due to

very few offline ties (with friends or neighbors) (Bargh & McKenna,

44

2004). The Internet and social networking site can act as a computer-

mediated communication channel that they can use to lower the barriers

to interacting with other people and at the same time encouraging them

to expose themselves (Bargh, McKenna, & Fitzsimons, 2002). These 4

hypotheses above is proposed to find out whether the effect of Facebook

on social capital varies with varying levels of life satisfaction (Diener,

Suh, & Oishi, 1997) and self-esteem (Rosenberg, 1989) which are the

most well-known measures to validate an individual’s well-being.

3.4 Scope

The scope of this research can be considered quite large as there are millions of

Facebook users in Indonesia. As discussed in Chapter 1 of this research, Indonesia has

one of the highest numbers of Facebook users worldwide. Indonesia is currently 4 th in

the list with just a little shy of 50 million active Facebook users. On the other hand,

Jakarta has the 2nd highest number of active Facebook users compared to all the other

cities around the world with almost 12 million users.

The researcher is located in Jakarta which is the perfect location to conduct this research

even though the expected respondents of this research is people reside in Jakarta as well

as any other city in Indonesia as this is a nationwide study. The number of respondents

targeted by the researcher for this research is 150-200 people due to the time limitation

of this research. The researcher will give out questionnaires as a way to collect data for

this research. Further details regarding the questionnaire will be discussed in the next

section of this chapter.

45

3.5 Data Collection

The researcher chose Questionnaires as the data collection technique for this research.

The reason behind choosing questionnaires to collect data is because this method offers

many advantages over other techniques such as:

o Quick to collect information

o Information can be collected from multiple respondents / group of people

simultaneously

o Information gathered is in a standardized format

3.5.1 Questionnaire Design

The questionnaire itself was based on the replicated journal “The Benefits of

Facebook “Friends”: Social Capital and College Students’ Use of Online Social

Network Sites” by Nicole B. Ellison, Charles Steinfeld and Cliff Lampe. The

author designed the questionnaire with the help of the one available in the replicated

journal. The questionnaire consists of 2 parts, first part requiring respondents to fill

demographic data such as:

a. Gender

b. Age

c. Education

d. Occupation,etc

46

3.5.2 Sample Likert Scale Questions

The second part of the questionnaire will be of likert scale questions. The author chose to

use this type of measurement because it is the most widely used non-comparative rating

scale. The advantage provided by using likert scale is that it allows for a certain gradation of

opinion and even no opinion at all rather than a simple yes or no answer from the

respondent. Besides that, it is easy for the researcher to constructs and administer and it is

easy for the respondent to understand Invalid source specified.. The data can then be

analyzed with ease through the quantitative data which is obtained. The author decided to

use the6 scales likert scale and eliminate the ‘neutral’ in order to avoid ambigous answers

by respondents.

3.6 Sampling Design

In conducting the data collection through the use of questionnaires, the researcher

decided to use a random sample. The target population is going to come from anyone

who has a Facebook account and reside anywhere in Indonesia. As people of varying

age, gender, income, etc. uses Facebook; it is more suitable to use a random sampling

method for this research. A random sampling technique will enable the researcher to get

a diverse response. As the amount of sample is quite small for this research, a diverse

result is considered better. The sample is going to constitute mostly of the researchers

friends and family, Binus International Students, Binus International Staff members as

well as random respondents that the researcher is able to reach.

47

3.7 Data Analysis

The data will be analyzed using SPSS 14 using statistical tools involving reliability test, validity

test, and regression, frequencies and cross tabulation.

3.7.1 Validity

Validity test is one of the most important test that needs to be carried out by every

author before doing a research. The aim of doing validity test is so that valid

conclusions about the effect of the independent variables on the dependent variables as

well as valid generalizations from the specific experimental environment to a larger

population can be made by the author (N.K.Malhotra, 2012). They type of validity test

the author decides to use is Pearson correlation. Validity is obeserved by seeing the

level of coherence of one variable against another as well as their relativity to make

sure that the research questions matches up with the researcher’s expectations.

3.7.2 Reliability

Reliability test is another important test that will also be carried out by the author. The

aim of this test is to ensure that the research produces consistent results if repeated

measurements are made (N.K.Malhotra, 2012) The author decided to use coefficient

alpha or Cronbach's alpha method to determine the internal consistency or average

correlation of items in a survey tool to measure its reliability. Cronbach's alpha is “a

numerical coefficient of reliability which is calculated by averaging the coefficients that

result from all possible combination of split halve” (N.K.Malhotra, 2012). Alpha is

calculated based on the reliability of a test as compared to other tests which measures

the same idea of insterest and has exactly the same number of items. The closer the

Cronbach’s alpha value is to 1, the higher the internal consistency reliability but values

above 0.6 is already acceptable.

48

3.7.3 Frequencies

The objective of the author in using frequency distribution is to obtain a count of the

number of responses associated with different variables, usually one variable at at time

(N.K.Malhotra, 2012)

3.7.4 Regression

Regression analysis is “a powerful and flexible procedure for analyzing associative

relationships between a metric dependent variable and one/ more metric independent

variables.” (N.K.Malhotra, 2012). This analysis will then show the relationships that

exist between a metric dependent variable and one or more independent variables.

Simple regression analysis is used in a situation where one independent variable is

hypothesized to affect one dependent variable whereas multiple regression analysis is

used in a situation where more than one independent variable is used to explain

variance in the dependent variable (Sekaran & Bougie, 2010).

3.7.5 Correlation

Correlation analysis measures the relationship between two items. The resulting value

(called the "correlation coefficient") shows if changes in one item will result in changes

in the other item. When comparing the correlation between two items, one item is called

the "dependent" item and the other the "independent" item. The goal is to see if a

change in the independent item (which is usually an indicator) will result in a change in

the dependent item (usually a security's price). This information helps you understand

an indicator's predictive abilities (Achelis, 2011).

49

CHAPTER IV

RESULTS & ANALYSIS

This chapter of the research is dedicated to show the results of the data collection

conducted as well as analyzing the data and see all the information that can be extracted

from it. All the data that has been gathered will be thoroughly analyzed and explained in

this chapter of the research.

This chapter will be divided into 4 different parts. The first part will discuss the

demographics of the respondents. Although this research and the hypothesis involved in

the framework has little to do with demographics, the researcher would like to include

them in order to provide better understanding of the respondents reached throughout

this research as well as easing interpretations and improve overall accuracy of the data

gathered. The second part of this chapter will discuss the reliability test conducted on

each variable used in this research, followed by the third part which discusses the

validity test of each sub-variable under the variable. The fourth and last part of the

chapter discusses the significance of each hypothesis by using regressions and then

drawing conclusions using the result from the regression analysis.

The data collection process was conducted within a span of 2 weeks. The questionnaire

was conducted online using Google Docs and shared to possible respondents via

Facebook and E-Mail. A total of 212 respondents answered the questionnaire, in which

12 was considered invalid as they are incomplete. The researcher used a mass approach

in reaching his respondents in order to reach the needed quota of 200 respondents

within a quite limited time span.

50

4.1 Demographic Frequencies

4.1.1 Gender Frequency of RespondentsGender

Frequency Percent Valid Percent

Cumulative

Percent

Valid Male 98 49.0 49.0 49.0

Female 102 51.0 51.0 100.0

Total 200 100.0 100.0

Table 4. 1 - Gender Frequency of Respondents

Figure 4. 1 - Gender Frequency of Respondents

From the table as well as the pie chart above, we can see that there is quite an

equal distribution of both male and female respondents with 49% (98 male) and

51% (102 female).

From this result, it can be concluded that Facebook is used equally by both male

and female.

51

4.1.2 Age Frequency of RespondentsAge


Cumulative

Percent

Valid <15 Yo 7 3.5 3.5 3.5

15-24 Yo 164 82.0 82.0 85.5

25-34 Yo 19 9.5 9.5 95.0

>34 Yo 10 5.0 5.0 100.0

Total 200 100.0 100.0

Table 4. 2 - Age Frequency of Respondents

Figure 4. 2 - Age Frequency of Respondents

The table and figure above shows the age proportion of this research i.e.- < 15 Years Old = 3.5% (7)- 15-24 Years Old = 82% (164)- 25-34 Years Old = 9.5% (19)- >34 Years Old = 5% (10)

52

4.1.3 Last Education Frequency of RespondentsLast Education


Cumulative

Percent

Valid High School 106 53.0 53.0 53.0

Diploma 5 2.5 2.5 55.5

Undergraduate 81 40.5 40.5 96.0

Midle Shcool 8 4.0 4.0 100.0

Total 200 100.0 100.0

Table 4. 3 - Last Education Frequency of Respondents

Figure 4. 3 - Last Education Frequency of Respondents

More than half of the respondents are high school graduates, covering 53%

(106) of the total respondents, followed by undergraduates with 40.5% (81). The

other two categories can be considered a minority as they only cover less than

10% of the number of respondents with 4% (8) of them being middle school

graduates and 2.5% (5) having a diploma.

53

4.1.4 Current Occupation Frequency of Respondents

Current Occupation


Cumulative

Percent

Valid Student 135 67.5 67.5 67.5

Employed 48 24.0 24.0 91.5

Entrepreneur 11 5.5 5.5 97.0

Unemployed 6 3.0 3.0 100.0

Total 200 100.0 100.0

Table 4. 4 - Current Occupation Frequency of Respondents

Figure 4. 4 - Current Occupation Frequency of Respondents

67.5% (135) of the respondents’ f this research is student, followed by 24% (48)

employed, 5.5% (11) entrepreneurs and 3% (6) unemployed or yet to find

employment.

54

4.1.5 Daily Internet Usage Frequency of Respondents

On average, how many hours do you spend on the Internet daily


Cumulative

Percent

Valid <1 Hour 7 3.5 3.5 3.5

1-2 Hours 39 19.5 19.5 23.0

2-3 Hours 45 22.5 22.5 45.5

>3 Hours 109 54.5 54.5 100.0

Total 200 100.0 100.0

Table 4. 5 - Daily Internet Usage Frequency of Respondents

Figure 4. 5 - Daily Internet Usage Frequency of Respondents

54.5% of the respondents are heavy internet users spending more than 3 hours

on the internet daily. 22.5% uses the internet in the range of 2-3 hours daily.

19.5% uses 1-2 hours of internet daily while only 3.5% uses less than an hour on

internet in a day.

55

4.2 Reliability & Validity Test

Before conducting any kind of analysis to reach a conclusion on whether to accept or

reject the hypothesis, the researcher will first conduct reliability and validity tests on the

construct being used in the survey which, in this case, would be the questionnaire.

Reliability will be measured using Cronbach’s Alpha; whereas validity will be

measured using corrected Item-Total Correlation.

4.2.1 Reliability Test

4.2.1.1 Intensity

Case Processing SummaryN %

Cases Valid 200 100.0

Excludeda 0 .0

Total 200 100.0

a. List wise deletion based on all variables in the procedure.

Table 4. 6 - Reliability Test (Case Processing Summary - Intensity)

Reliability StatisticsCronbach's

Alpha N of Items

.867 6Table 4. 7 - Cronbach's Alpha (Intensity)

The Cronbach Alpha is 0.867, which is higher than the

acceptable level of 0.6; hence it can be concluded that the

questions in this section are reliable enough to measure the

“Intensity” variable.

56

4.2.1.2 Self Esteem



Excludeda 0 .0

Total 200 100.0


Table 4. 8 - Reliability Test (Case Processing Summary - Self-Esteem)


Alpha N of Items

.790 7Table 4. 9 - Cronbach's Alpha (Self-Esteem)

The Cronbach Alpha is 0.790, which is higher than the acceptable

level of 0.6; hence it can be concluded that the questions in this

section are reliable enough to measure the “Self-Esteem”

variable.

4.2.1.3 Life Satisfaction



Excludeda 0 .0

Total 200 100.0


Table 4. 10 - Reliability Test (Case Processing Summary - Life Satisfaction)

57


Alpha N of Items

.859 5Table 4. 11 - Cronbach's Alpha (Life Satisfaction)




“Life Satisfaction” variable.

4.2.1.4 Bridging Social capital



Excludeda 0 .0

Total 200 100.0


Table 4. 12 - Reliability Test (Case Processing Summary - Bridging Social Capital)


Alpha N of Items

.894 8Table 4. 13 - Cronbach's Alpha (Bridging Social Capital)




“Bridging Social capital” variable.

58

4.2.1.5 Bonding Social Capital



Excludeda 0 .0

Total 200 100.0


Table 4. 14 - Reliability Test (Case Processing Summary - Bonding Social Capital)


Alpha N of Items.712 5

Table 4. 15 - Cronbach's Alpha (Bonding Social Capital)




“Bonding Social Capital” variable.

59

4.2.2 Validity Test

In this study, the significance level of 5% is used and the number of samples (n)

100 with df = n-2 = 200-2 = 198 so r table value used is 0.139.

4.2.2.1 IntensityItem-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Intensity1 13.9000 9.447 .824 .819

Intensity2 14.2500 10.168 .542 .866

Intensity3 13.9000 9.528 .729 .833

Intensity4 14.2900 9.232 .659 .847

Intensity5 14.1100 10.350 .576 .859

Intensity6 13.8500 9.354 .686 .841Table 4. 16 - Validity Test (Intensity)

From the table above it can be seen that the value of r or Corrected

Item-Total Correlation for each of the items is bigger when compared to

the r table value (0.139). From this, it can be concluded that all the

items or questions in the "Intensity" variable is already valid.

4.2.2.2 Self Esteem Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Self-Esteem1 18.4700 7.074 .551 .758

Self-Esteem2 18.3950 7.074 .637 .746

Self-Esteem3 18.4800 7.527 .257 .820

Self-Esteem4 18.4900 7.136 .528 .762

Self-Esteem5 18.5100 7.025 .402 .790

Self-Esteem6 18.3600 6.694 .693 .732

Self-Esteem7 18.3850 6.308 .691 .727Table 4. 17 - Validity Test (Self-Esteem)

60

From the table above it can be seen that the value of r or Corrected Item-

Total Correlation for each of the items is bigger when compared to the r

table value (0.139). From this, it can be concluded that all the items or

questions in the "Self-Esteem" variable is already valid.

4.2.2.3 Life Satisfaction

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

LifeSatisfaction1 11.5450 5.485 .618 .844




LifeSatisfaction5 11.9600 4.431 .693 .833Table 4. 18 - Validity Test (Life Satisfaction)


Total Correlation for each of the items is bigger when compared to the r

table value (0.139). From this, it can be concluded that all the items or

questions in the "Life Satisfaction" variable is already valid.

61

4.2.2.4 Bridging Social capital

Table 4. 19 - Validity Test (Bridging Social Capital)

From the table above it can be seen that the value of r or Corrected

Item-Total Correlation for each of the items is bigger when compared to

the r table value (0.139). From this, it can be concluded that all the

items or questions in the "Bridging Social Capital" variable is already

valid.

4.2.2.5 Bonding Social Capital

62


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Bridging1 21.6900 10.798 .772 .871

Bridging2 21.6350 11.972 .558 .890

Bridging3 21.8250 11.271 .538 .895

Bridging4 21.5750 11.190 .697 .878

Bridging5 21.6300 10.707 .778 .870

Bridging6 21.7200 10.866 .773 .871

Bridging7 21.7950 10.847 .639 .885

Bridging8 21.5900 11.097 .663 .881

Table 4. 20 - Validity Test (Bonding Social Capital)


Total Correlation for each of the first 4 items is bigger when compared to

the r table value (0.139). From this, it can be concluded that all the items

or questions other than Bonding5 in the "Bonding Social Capital"

variable is already valid.

4.4 Hypothesis Testing

4.4.1 Simple Linear Regression

H1 - Intensity of Facebook use will be positively associated with individuals’ perceived

bonding social capital.

63


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Bonding1 11.9750 3.683 .726 .558

Bonding2 12.3250 3.929 .467 .666

Bonding3 11.9900 3.698 .731 .557

Bonding4 12.0650 4.222 .566 .631

Bonding5 12.1650 5.304 .036 .836

Figure 4. 6 - Submodel Hypothesis 1

Variables Entered/Removedb

Model Variables Entered Variables Removed Method

dimension0

1 Intensitya . EnterTable 4. 21- Hypothesis 1 Variables

a. All requested variables entered.

b. Dependent Variable: Bonding Social Capital

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients

t Sig.B Std. Error Beta

1 (Constant) 2.202 .153 14.419 .000

Intensity .293 .053 .366 5.527 .000Table 4. 22 - Hypothesis 1 Regression

a. Dependent Variable: Bonding Social Capital

Regression equation for the above table is:

Bonding Social Capital = 2,202 + 0,293(Intensity)

Influence of Intensity variable on Bonding Social Capital.

From the above table, it is known that the ”t” value for Intensity variable is

5.527 at a significance level of 0.000 with a regression coefficient (β) of +0.293.

Because the significance value 0.000 < 0.05 ( = 5%) it can be concluded that

the intensity variable significantly and positively affects Bonding Social Capital.

In other words, the higher the Intensity variable, Bonding Social Capital variable

will also be higher. Thus, the first hypothesis (H1) which states that “Intensity

64

of Facebook use will be positively associated with individuals’ perceived

bonding social capital” is supported/accepted.

.

H2 - Intensity of Facebook use will be positively associated with individuals’ perceived

bridging social capital.

Figure 4. 7 - Submodel Hypothesis 2



dimension0

1 Intensitya . Enter

Table 4. 23 - Table 4. 22 - Hypothesis 1 Regression


b. Dependent Variable: Bridging Social Capital

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients


1 (Constant) 1.947 .133 14.636 .000

Intensity .409 .046 .532 8.849 .000Table 4. 24 - Hypothesis 2 Regression

a. Dependent Variable: Bridging Social Capital

Regression equation for the above table is:

Bridging Social Capital = 1,947 + 0,409(Intensity)

Influence of Intensity variable on Bridging Social Capital.

65

From the above table, it is known that the “t” value for Intensity variable is

8,849 at a significance level of 0.000 with a regression coefficient (β) of +0,409.

Because the significance value 0.000 < 0.05 ( = 5%) it can be concluded that

the Intensity variable significantly and positively affects Bridging Social

Capital. In other words, the higher the Intensity variable, Bridging Social Capital

variable will also be higher. Thus, the second hypothesis (H2) which states that

“Intensity of Facebook use will be positively associated with individuals’

perceived bridging social capital” is supported/accepted.

4.4.2 Moderated Regression Analysis

H3a – The relationship between intensity of Facebook use and bonding social capital

will vary depending on the degree of a person’s satisfaction with life.

66

Figure 4. 8 - Submodel Hypothesis 3a



dimension0

1 Life-Satisfaction*Intensity, Intensitya . Enter

Table 4. 25- Hypothesis 3a Variables



From the above table, it is known that the “t” value for moderating variable (Life-

satisfaction*Intensity) is 21,014 at a significance level of 0.000 with a regression

coefficient (β) of +0,177. Because the significance value 0.000 < 0.05 ( = 5%) it

can be concluded that Life-Satisfaction significantly and positively affect the

relationship between Intensity and Bonding Social Capital. Thus, this hypothesis

(H3a) which states that “The relationship between intensity of Facebook use and

bonding social capital will vary depending on the degree of a person’s satisfaction

with life.” is supported/accepted.

H3b - The relationship between intensity of Facebook use and bridging social capital

will vary depending on the degree of a person’s satisfaction with life.

67

Coefficientsa

Model


Standardized

Coefficients

T Sig.B Std. Error Beta

1 (Constant) 1.445 .092 15.655 .000

Intensity -.026 .033 -.032 -.779 .437

Life-Satisfaction*Intensity .177 .008 .870 21.014 .000Table 4. 26 - Hypothesis 3a Regression


Figure 4. 9 - Submodel Hypothesis 3b



dimension0


Table 4. 27 - Hypothesis 3b Variables



Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 1.482 .117 12.638 .000

Intensity .213 .042 .277 5.046 .000

Life-Satisfaction*Intensity .109 .011 .559 10.173 .000Table 4. 28 - Hypothesis 3b Regression


From the above table, it is known that the “t” value for moderating variable

(Life-satisfaction*Intensity) is 10,173 at a significance level of 0.000 with a

regression coefficient (β) of +0,109. Because the significance value 0.000 < 0.05

( = 5%) it can be concluded that Life-Satisfaction significantly and positively

affect the relationship between Intensity and Bridging Social Capital. Thus, this

68

hypothesis 3b (H3b) which states that “The relationship between intensity of

Facebook use and bridging social capital will vary depending on the degree of

a person’s satisfaction with life” was supported/accepted.

H4a - The relationship between intensity of Facebook use and bonding social capital

will vary depending on the degree of a person’s self-esteem.

Figure 4. 10 - Submodel Hypothesis 4a

69



dimension0

1 Self-Esteem*Intensity, Intensitya . EnterTable 4. 29 - Hypothesis 4a Variables



From the above table, it is known that the “t” value for moderating variable (Self-

Esteem*Intensity) is 8,746 at a significance level of 0.000 with a regression


can be concluded that Self-Esteem significantly and positively affect the

relationship between Intensity and Bonding Social Capital. Thus, this hypothesis 4a

(H4a) which states that “The relationship between intensity of Facebook use and

bonding social capital will vary depending on the degree of a person’s self-

esteem” was supported/accepted.

H4b - The relationship between intensity of Facebook use and bridging social capital

will vary depending on the degree of a person’s self-esteem.

70

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 1.761 .139 12.642 .000

Intensity .040 .054 .050 .752 .453

Self-Esteem*Intensity .120 .014 .585 8.746 .000Table 4. 30 - Hypothesis 4a Regression


Figure 4. 11 - Submodel Hypothesis 4b



dimension0

1 Self-Esteem*Intensity, Intensitya . EnterTable 4. 31 - Hypothesis 4b Variables



From the above table, it is known that the “t” value for moderating variable (Self-

Esteem*Intensity) is 20,398 at a significance level of 0.000 with a regression


71

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 1.350 .081 16.644 .000

Intensity .066 .031 .086 2.110 .036

Self-Esteem*Intensity .163 .008 .828 20.398 .000Table 4. 32 - Hypothesis 4b Regression


can be concluded that Self-Esteem significantly and positively affect the

relationship between Intensity and Bridging Social Capital. Thus, this hypothesis 4b

(H4b) which states that “The relationship between intensity of Facebook use and

bridging social capital will vary depending on the degree of a person’s self-

esteem” was supported/accepted.

4.4.3 Correlations

4.4.3.1 Correlation between Intensity and Bonding Social Capital

Correlations

Intensity

Bonding Social

Capital

Intensity Pearson Correlation 1 .366**

Sig. (2-tailed) .000

N 200 200

Bonding Social Capital Pearson Correlation .366** 1


N 200 200Table 4. 33 - Hypothesis 1 Correlation

**. Correlation is significant at the 0.01 level (2-tailed).

72

From the above table, it can be seen that the r value of the Pearson

Correlation obtained is 0.366 with a significance value of 0.000. Because the

significance value is less than 0.05, it can be concluded that there is a

positive and significant relationship between Intensity and Bonding Social

Capital.

4.4.3.2 Correlation between Intensity and Bridging Social Capital

Correlations

Intensity

Bridging Social

Capital



N 200 200

Bridging Social Capital Pearson Correlation .532** 1


N 200 200Table 4. 34 - Hypothesis 2 Correlation

**. Correlation is significant at the 0.01 level (2-tailed).From the above table, it can be seen that the r value of the Pearson

Correlation obtained is 0,532 with a significance value of 0.000. Because the

significance value is less than 0.05, it can be concluded that there is a

positive and significant relationship between Intensity and Bridging Social

Capital.

4.4.4 R2 (Coefficient of Determination) & ANOVA (Analysis of Variance) Analysis

R2 or coefficient of determination is used to look at the contribution of the

independent variables towards the dependent variable. The higher the Adjusted

73

R Square, the better the regression model as it means that the independent

variable was able to explain the dependent variable.

ANOVA on the other hand, shows whether or not significant difference exist

between the variables tested. To indicate that significant statistical difference is

present, the significance level of a dependent variable must not exceed 0.05. The

significance level is located in the ANOVA table under the label “Sig”.

Hypothesis 1 Model Summary

ModelR R Square Adjusted R Square Std. Error of the Estimate

1 .366a .134 .129 .45993

Table 4. 35 - R-Square Analysis Hypothesis

74

Model Summary

ModelR R Square Adjusted R Square Std. Error of the Estimate

1 .366a .134 .129 .45993

From the table above, the impact of Intensity on Bonding Social Capital is shown

by the value of the coefficient of R Square is 0. 134, this means that the variation

in the variable Bonding Social Capital can be explained by the variable Intensity

by 13.4% The remaining 86.6% is the contribution of other independent variables

that are / are not included in this study. In other words, there are more factors

affecting Bonding Social Capital Intensity. But however, the variable Intensity is

good and is able to explain Bonding Social Capital, R2 value shows the model fit

that is the capability of the data in predicting the variable which in this case means

the data has an average prediction capability (13.4%).

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 6.461 1 6.461 30.543 .000a

Residual 41.884 198 .212

Total 48.345 199 Table 4. 36 - ANOVA Analysis Hypothesis 1 a. Predictors: (Constant), Intensity

a. Dependent Variable: Bonding Social CapitalThe author used F-test analysis to determine whether or not Intensity has an impact

on Bonding Social Capital. Upon calculation, the F-test value was found to be

30.543 with a probability (Sig.) of 0.000. This shows that there is a good

relationship between Intensity and Bonding Social Capital.

Hypothesis 2

75

Model Summary

Model

R R Square

Adjusted R

Square Std. Error of the Estimate

dimension0

1 .532a .283 .280 .40077Table 4. 37 - R-Square Analysis Hypothesis 2

a. Predictors: (Constant), Intensity

From the table above, the impact of Intensity on Bridging Social Capital is shown by

the value of the coefficient of R Square is 0. 283, this means that the variation in the

variable Bonding Social Capital can be explained by the variable Intensity by 28.3%

The remaining 71.7% is the contribution of other independent variables that are / are not

included in this study. In other words, there are more factors affecting Bridging Social

Capital Intensity. But however, the variable Intensity is good and is able to explain

Bridging Social Capital, R2 value shows the model fit that is the capability of the data in

predicting the variable which in this case means the data has a good prediction

capability (13.4%).

ANOVAb


1 Regression 12.578 1 12.578 78.311 .000a

Residual 31.802 198 .161

Total 44.380 199Table 4. 38 - ANOVA Analysis Hypothesis 2



The author used F-test analysis to determine whether or not Intensity has an impact on

Bridging Social Capital. Upon calculation, the F-test value was found to be 78.311 with

a probability (Sig.) of 0.000. This shows that there is a good relationship between

Intensity and Bridging Social Capital.

76

H3AModel Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

dimension0

1 .856a .733 .730 .25610

Table 4. 39 - R-Square Analysis Hypothesis 3a

a. Predictors: (Constant), Life-Satisfaction*Intensity, Intensity

The Model Summary table shows that Intensity can explain 73.3% of variance in

Bonding Social Capital after introducing Life Satisfaction as the moderating

variable. The variable Intensity moderated with Life Satisfaction is quite good

and able to explain Bonding Social Capital; R2 value shows the model fit that is

the capability of the data in predicting the variable which in this case means the

data has a strong prediction capability (73.3%).

ANOVAb

Model

Sum of Squares df

Mean

Square F Sig.

1 Regression 35.424 2 17.712 270.054 .000a

Residual 12.921 197 .066

Total 48.345 199Table 4. 40 - ANOVA Analysis Hypothesis 2



From the table above, it can clearly be seen that the relationship between Intensity and

Bonding Social Capital is quite significant after being moderated by Life Satisfaction

variable. Upon calculation, the F-test value was found to be 270.054 with a probability

77

(Sig.) of 0.000. This shows that there is a good relationship between Intensity and

Bonding Social Capital moderated with Life Satisfaction.

H3B

Model Summary


dimension0

1 .728a .530 .525 .32532Table 4. 41 - R-Square Analysis Hypothesis 3b



Bridging Social Capital after introducing Life Satisfaction as the moderating variable.

The variable Intensity moderated with Life Satisfaction is quite good and able to

explain Bridging Social Capital; R2 value shows the model fit that is the capability of

the data in predicting the variable which in this case means the data has a strong

prediction capability (53.0%).

ANOVAb


1 Regression 23.531 2 11.765 111.168 .000a

Residual 20.849 197 .106

Total 44.380 199Table 4. 42 - ANOVA Analysis Hypothesis 3b




Bridging Social Capital is quite significant after being moderated by Life Satisfaction


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Bonding Social Capital moderated with Life Satisfaction.

H4A

Model Summary


dimension0

1 .613a .376 .370 .39134Table 4. 43 - R-Square Analysis Hypothesis 4a

a. Predictors: (Constant), Self-Esteem*Intensity, Intensity


Bonding Social Capital after introducing Self-Esteem as the moderating variable. The

variable Intensity moderated with Self-Esteem is quite good and able to explain

Bonding Social Capital; R2 value shows the model fit that is the capability of the data

in predicting the variable which in this case means the data has a good prediction

capability (37.6%).

ANOVAb


1 Regression 18.174 2 9.087 59.336 .000a

Residual 30.170 197 .153

Total 48.345 199Table 4. 44 - ANOVA Analysis Hypothesis 4a




Bonding Social Capital is quite significant after being moderated by Self-Esteem

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Bonding Social Capital moderated with Self-Esteem.

H4B

Model Summary


dimension0

1 .877a .770 .767 .22776Table 4. 45 - R-Square Analysis Hypothesis 4b



Bridging Social Capital after introducing Self-Esteem as the moderating variable. The

variable Intensity moderated with Self-Esteem is quite good and able to explain

Bridging Social Capital; R2 value shows the model fit that is the capability of the data

in predicting the variable which in this case means the data has a strong prediction

capability (77.0%).

ANOVAb


1 Regression 34.161 2 17.081 329.275 .000a

Residual 10.219 197 .052

Total 44.380 199Table 4. 46 - ANOVA Analysis Hypothesis 4b




Bridging Social Capital is quite significant after being moderated by Self-Esteem

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Bonding Social Capital moderated with Self-Esteem.

CHAPTER V

DISCUSSION

This chapter will summarize and conclude the result of the result that has been

elaborated in the previous chapter. Besides concluding the study, the researcher will

also discuss whether or not the research objective(s) which was discussed in the first

chapter of this study is answered by the study that has been conducted.

5.1 Discussion

Table 5.1 below is based on the statistical analysis conducted on the study. The

table below consist of the hypothesis number (For example: H1, H2, H3a, etc.),

the variable(s) involved in that hypothesis, the moderating variables used in the

hypothesis, the R2 result, F value, Significance level (Sig.), Correlation analysis

result as well as the result of the hypothesis itself (Accepted or Rejected).

The table below will be further discussed by the researcher to describe the

results of the

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Hypothesis Variable Moderator R2 F Sig. Correlatio

n

Result

H1Intensity

- Bonding

- .134 30.543 .000a

.366** Accepted

H2Intensity

- Bridging

- .283 78.311 .000a .532** Accepted

H3aIntensity

- Bonding

Life Satisfaction

.733270.05

4.000a - Accepted

H3bIntensity

- Bridging

Life Satisfaction

.530111.16

8.000a - Accepted

H4aIntensity

- Bonding

Self-Esteem

.376 59.336 .000a - Accepted

H4bIntensity

- Bridging

Self-Esteem

.770329.27

5.000a - Accepted


Table 5. 1 - Summary of SPSS Analysis

As we can see from the table above, all 6 hypotheses involved in the model /

framework has been accepted. This means that the model is very good in

predicting and/or determining as well as answering the research questions stated

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in the beginning of this study. At the same time, as all the hypotheses are

accepted; the only way to differentiate / determine the significance of each

relationship is by looking at the results or the values obtained from the statistical

analysis which has been summarized in the table above.

Hypothesi

s

Variable Moderator R2 F Sig. Correlation Result

H1Intensity

- Bonding

- .134 30.543 .000a

.366** Accepted

H2Intensity

- Bridging

- .283 78.311 .000a .532** Accepted


Table 5. 2 - Summary of Hypothesis Result 2

Comparing the relationship between Intensity of Facebook use with Bonding

or Bridging can be seen from the R2 value, F value as well as the result of the

correlation analysis. The relationship between Intensity of Facebook use

with Bonding Social Capital obtained an R2 of 0.134 or 13.4%. This means

that Bonding Social Capital can only explain 13.4% of the variance in the

Intensity variable. On the other hand, Bridging Social Capital obtained an

R2 value of 0.283 or 28.3%. This means that Bridging Social Capital can

explain up to 28.3% of the variance in the Intensity variable. From this

alone, we can conclude that Bridging Social Capital is more interconnected

with the Intensity of Facebook use. Using the F value to determine which

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relationship is more significant has led to the same conclusion that Intensity

of Facebook use has a more significant relationship with Bridging Social

Capital compared to Bonding Social Capital. Relationship between Intensity

of Facebook use and Bonding Social Capital obtained an F value of 30.543

while Bridging Social Capital obtained 78.311. Again, Bridging Social

Capital proved to have a much more significant relationship with Intensity of

Facebook use. Correlation Analysis was also conducted to compare the

correlation of Intensity of Facebook use with both dependent variables,

Bonding and Bridging Social Capital. Bonding Social Capital obtained 0.366

while Bridging Social Capital obtained 0.532 when correlated to Intensity of

Facebook use. This shows that Bridging Social Capital is more correlated to

Intensity of Facebook Use.

All the statistical analysis conducted have proven that the relationship

between Intensity of Facebook use with Bridging Social Capital is more

significant compared to Bonding Social Capital. This means that the

intensity of an individual’s Facebook usage will help an individual more in

bridging their social capital, or in other words; this study have proven that

the intensity of an individual’s Facebook use will affect these individual’s

weaker ties, creating stronger relationship with other social beings on

Facebook which is harder to come by for many individuals. Bridging Social

Capital is an important part of a person’s social capital; it exposes an

individual to diverse information which will keep an individual growing,

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changing, as well as inventing themselves individually and socially.

Bridging social capital is also critical in building mutual respect, empathy

and understanding. Bridging Social Capital is a source of diversity and

provides real value for individual’s civic health (Cobb, 2011) (Burke, Kraut,

& Marlow, Social Capital on Facebook: Differentiating Uses and Users,

2011).

The results of the first and second hypothesis have been thoroughly

explained above. However, these two hypotheses does not include the

indices of psychological well-being i.e. self-esteem and satisfaction with life

which are an important part of this study. Apart from trying to find out the

type of social capital affected through the intensity of an individual’s

Facebook use, this study is also trying to discover whether an individual’s

psychological well-being affects or play a part in determining the type of

social capital affected through the intensity of Facebook use. “In the past

decade, a number of studies have explored how Internet use might be related

to psychological and social well-being with mixed results (e.g., Kraut et al.,

1998; Kraut et al., 2002; McKenna & Bargh, 2000; Nie, 2001; Shaw& Gant,

2002; Valkenburg & Peter, 2007)” (Steinfeld, Lampe, & Ellison, 2008).

Some results from the above examples have proven that intense internet use

is associated with loneliness, depression and stress. On the other hand, there

were also several results that has proven that internet have positive impacts

on psychological well-being as online interactions was able to mitigate any

85

loss of direct or offline communication with others due to the time spent

online (Steinfeld, Lampe, & Ellison, 2008).

There were also experiments that have shown that online engagements have

decreased perceived loneliness as well as depression while at the same time

increases social support and self-esteem. Another study has proven that

adolescents who are socially anxious have also found internet to be far more

valuable for intimate communication or relationship (Steinfeld, Lampe, &

Ellison, 2008).

As per this study, below are the statistical results we have gathered

Hypothesis Variable Moderator R2 F Sig. Correlatio

n

Result

H3aIntensity

- Bonding

Life Satisfaction

.733270.05

4.000a - Accepted

H3bIntensity

- Bridging

Life Satisfaction

.530111.16

8.000a - Accepted

H4aIntensity

- Bonding

Self-Esteem

.376 59.336 .000a - Accepted

H4bIntensity

- Bridging

Self-Esteem

.770329.27

5.000a - Accepted

Table 5. 3 - Summary of Hypothesis Result 3

86

This study have also proven that psychological well-being play a part in

determining what type of social capital affected through the use of social

media; in this case, Facebook. The results of this study which can be seen in

Table 5.3 have proven that psychological factors (self-esteem and life

satisfaction) significantly affect the relationship between Intensity of

Facebook use with Bonding as well as Bridging Social Capital.

From the table above (Table 5.3), we can see that the hypotheses are

accepted; this means that psychological factors such as self-esteem and life

satisfaction play a significant role in the overall model/framework.

According to the results obtained, Bonding Social Capital is more affected

by individual’s satisfaction with life compared to their self-esteem. This

conclusion was derived after seeing the R2 results obtained from the

statistical analysis previously conducted. The R2 obtained when putting Life

Satisfaction as a moderating factor between Intensity and Bonding social

capital was 0.73 or 73% while Self-Esteem was only able to obtain 0.376 or

37.6% when acting as a moderating factor between Intensity and Bonding

Social Capital. The conclusion that can be drawn from this result is that

people with high life satisfaction uses Facebook more to maintain stronger

ties with family and close friends compared to people with high self-esteem.

On the other hand, people with high self-esteem are able to affect Bridging

Social Capital more than people with high life satisfaction. With R2 value of

0.77 or 77%, it can be concluded that Self-Esteem plays a significant role in

affecting the relationship between Intensity of Facebook use and Bridging

87

Social Capital. Life satisfaction was only able to get 0.53 or 53% when used

as a moderating factor between Intensity of Facebook use and Bridging

Social Capital.

In conclusion people with higher life satisfaction tend to use Facebook more

to maintain their strong ties with close friends and family while people with

high self-esteem is confident enough to maintain and strengthen weaker ties

through Facebook.

Looking at the F value and significance level of both moderating variable

(self-esteem and life satisfaction), it is quite clear that both moderating

variable has a quite significant impact on the relationship between intensity

of Facebook use with both Bridging and Bonding Social Capital. Life

satisfaction as a moderating factor was able to obtain an F value of 270.054

and 111.168 against Bonding and Bridging Social Capital respectively. At a

significance level of .000a, both results mean that Life Satisfaction has quite

an impact on both the relationships (Intensity – Bonding and Intensity –

Bridging). Self-Esteem also made quite an impact on both the relationships

mentioned above by obtaining an F value of 59.336(Intensity – Bonding)

and 329.275 (Intensity – Bridging) at a significance value of .000a. Like the

previous analysis, this analysis also has a similar conclusion that both

moderating variables has quite an impact on the relationship between

Intensity of Facebook use and Bridging Social Capital as well as the

relationship between Intensity of Facebook use and Bonding Social Capital.

88

This study has successfully proven not only that psychological factor(s)

affect the type of Social Capital affected through use of Facebook, but it has

also proven that these psychological factors has a quite significant effect on

the relationship between intensity of Facebook use and Bridging or Bonding

Social Capital itself.

The same conclusion was brought about by Valkenburg et al. in the year

2006 as well as Kraut et al. in the year 2002 (Valkenburg, Peter, &

Schouten, 2006) (Kraut, Kiesler, Boneva, Cumming, Helgeson , &

Crawford, 2002).

5.2 Additional Information

Measures of Facebook usage to meet new people & connect with existing offline contacts:

[I have used Facebook to check out someone I met socially]

Frequency Percent Valid Percent Cumulative Percent

Valid Strongly Disagree 9 4.5 4.5 4.5

Disagree 19 9.5 9.5 14.0

Agree 132 66.0 66.0 80.0

Strongly Agree 40 20.0 20.0 100.0

Total 200 100.0 100.0

Table 5. 4- I have used Facebook to check out someone I met socially

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Figure 5. 1 - I have used Facebook to check out someone I met socially

This measures the number of people (out of 200) who have used Facebook to check out

someone he/she have met socially. This can be considered a measure of bridging social

capital through Facebook as connecting with a person you just met socially means

trying to strengthen a ‘weak tie’ which is clearly considered bridging social capital.

Through the result above it is quite clear that there is quite a strong bridging social

capital potential through Facebook.

[I use Facebook to learn more about other people in my class / workplace]



Disagree 32 16.0 16.0 18.0

Agree 120 60.0 60.0 78.0

Strongly Agree 44 22.0 22.0 100.0

Total 200 100.0 100.0

Table 5. 5 - I use Facebook to learn more about other people in my class / workplace

90

Figure 5. 2 - I use Facebook to learn more about other people in my class / workplace

The result above is trying to show how many people have used Facebook to learn more

about people in his/her class/workplace. This can be considered a bonding social capital

scale as people in his/her class or workplace would mean that he/she already has an

established connection or tie with the person. Hence, the result above proves how many

people use Facebook to ‘bond’ with people in their class/workplace. In conclusion,

there is also a quite significant bonding social capital potential through Facebook.

[I use Facebook to learn more about other people living near me]



Disagree 52 26.0 26.0 29.5

Agree 113 56.5 56.5 86.0

Strongly Agree 28 14.0 14.0 100.0

Total 200 100.0 100.0

Table 5. 6 - I use Facebook to learn more about other people living near me

91

Figure 5. 3 - I use Facebook to learn more about other people living near me

The result above can be considered both a scale of bonding as well as bridging social

capital. “Using Facebook to learn more about people living near me” failed to specify if

the individual already know the person or the ‘person living near me’ individual is the

new owner of a house/apartment in the neighborhood. Hence, this scale can be

classified as a scale to measure both bonding and bridging social capital. The result of

the scale above shows that social capital has a high potential of getting affected through

Facebook.

[I use Facebook to keep in touch with my old friends]



Disagree 6 3.0 3.0 4.0

Agree 113 56.5 56.5 60.5

Strongly Agree 79 39.5 39.5 100.0

Total 200 100.0 100.0

Table 5. 7 - I use Facebook to keep in touch with my old friends

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Figure 5. 4 - I use Facebook to keep in touch with my old friends

The scale above purely measures bonding social capital that occurs through Facebook.

The name of the scale itself which is, “I use Facebook to keep in touch with my old

friends” clearly shows that there is already an established strong bond between the

individuals involved. The result above shows that bonding social capital is quite strong

when it comes to keeping in touch with old friends through Facebook.

[I use Facebook to meet new people]



Disagree 83 41.5 41.5 64.5

Agree 54 27.0 27.0 91.5

Strongly Agree 17 8.5 8.5 100.0

Total 200 100.0 100.0

Table 5. 8 - I use Facebook to meet new people

93

Figure 5. 5 - I use Facebook to meet new people

Unlike the scale above, this scale is purely trying to measure bridging social capital that

occurs through Facebook. In terms of this scale, “meet new people” means that this can

be considered the purest kind of bridging social capital there is and the result shows that

there is quite a mixed response from the respondents. Nevertheless, this purest scale of

bridging of social capital was able to get 35.5%. This means that more than one-third of

the respondents use this purest kind of bridging social capital through Facebook which

is quite a significant result in the point of view of Bridging Social Capital through

Facebook.

CHAPTER VI

CONCLUSION & RECOMMENDATION

This chapter will summarize and conclude all the analysis, result and interpretations that

have been elaborated in the previous chapter of the research. The objective of this

94

chapter is to conclude the entire study and discuss the research questions that have been

answered as well as the objectives this research were able to reach. At the end of the

chapter, the researcher will also discuss the limitations of the current research and

provide future research recommendations.

6.1 Conclusion

This study titled “Social Capital on Facebook: Bonding or Bridging

Relationships between Individuals?” has reached; in one way or another, all the

objectives of the study mentioned in the beginning of this study.

All the analysis, results and interpretations discussed in the previous chapter as

well as the conclusions drawn above have been derived from this research. The

discussions of the results in the previous chapter were also able to answer all of

the research objectives as well as research questions mentioned in the beginning

(Chapter 1) of this research.

The research questions answered are as follows:

Research Question 1

Does the level of intensity of an Individual’s Facebook use affect his/her

perceived social capital? - YES

Research Question 2

95

What type of an individual’s social capital (bridging or bonding) is

affected by using Facebook to communicate and socialize? – BOTH

BRIDGING & BONDING SOCIAL CAPITAL AFFECTED.

BRIDGING SOCIAL CAPITAL MORE SIGNIFICANTLY

AFFECTED.

Research Question 3

Does the intensity of Facebook use have a positive impact on an

individual’s perceived bridging social capital? - YES

Research Question 4

Does the intensity of Facebook us have a positive impact on an

individual’s perceived bonding social capital? - YES

Research Question 5

Is an individual’s life satisfaction and self-esteem a factor in the level of

social capital (bridging or bonding) affected through the intensity of

his/her Facebook use? – YES

The objectives of this research which have been reached by this study are as

follows:

- This study has been able to prove that Intensity of Facebook use actually

affects an individual’s social capital. At the same time, this study has also been

able to prove that Bridging Social Capital is more significantly affected by

intensity of Facebook use compared to Bonding Social Capital.

96

In terms of an individual’s psychological well-being, this study have proven that

they do play a role in affecting not only the level of social capital affected

through the use of Facebook but this study have also proved that an individual’s

psychological well-being also affect the type of social capital affected.

6.2 Limitation

Due to the limited time and resources available for the researcher to conduct the

research, there are a few unavoidable limitations which the researcher would

like to discuss:

The researcher was only able to use questionnaires as the method of data

collection due to the limited resources available to the researcher.

The researcher was only able to get 200 respondents which are not quite

enough to prove the accuracy of this study.

The demographic results obtained from the sample(s) are not diverse

enough for comparison and hypothesis testing. The demographic results

shown in this research are just to inform the readers of the respondents’

demography.

Due to the researcher’s limited knowledge on data analysis, the

researcher could only conduct simple linear regression instead of

multiple linear regression which might have improved the results of the

data analysis and improve the research as a whole.

97

6.3 Future Research Recommendations

Here are a few recommendations the researcher would like to provide future

researchers who are conducting a research on this topic:

Try to wisely utilize the time provided in conducting the research to

collect more data and information available from different sources.

In order to improve data accuracy, future researchers can expand the

sample size

Try to collect data from diverse respondents in order to be able to use the

demographics for comparison and hypothesis testing.

Prior to conducting his/her research, future researchers should maximize

their knowledge on data analysis in order to be able to perform a much

needed multiple linear regression and/or other data analysis method to be

able to provide the best analytical result and extract all the information

possible from the data obtained throughout the data collection process.

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Appendix

Appendix 1 - Questionnaire

Respected respondent, My Name is Mohit Kanayolal from Binus International University. I am currently doing my research in order to complete my undergraduate study. My research topic is “Social Capital on Facebook – Bridging or Bonding relationships between individuals. A preliminary study in Indonesia”. I need your participation by filling this questionnaire for my research. Thank you very much for your time and participation in filling out this questionnaire.

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Are you a Facebook user?

A. Yes B. No

If your answer to the above question is “No”, thank you for your attention and participation.

If “Yes” please proceed by answering the following questions:

1. Sex?A. MaleB. Female

2. Age?

A. <15 B. 15-24

C. 25-34 D. >343. Last Education?

A. High School/SMA B. Diploma/D3C. Undergraduate/S1 D. Graduate/S2E. Other: ___________

4. Current Occupation?

A. Student B. EmployedC. Entrepreneur D. UnemployedE. Other: __________

5. Residence:A. JakartaB. Outside Jakarta, Please Specify: ____________

6. On average, how many hours do you spend on the Internet daily?

A. < 1 Hour B. 1 – 2 HoursC. 2 – 3 Hours D. > 3 Hours

7. On average, how many minutes per day have you spent on Facebook

A. Less than 10 B. 10 – 30C. 31 – 60 D. 1 – 2 HoursE. 2 -3 Hours F. > 3 Hours

8. How many Facebook “Friends” do you have at the moment?

A. < 10 B. 11 – 50

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C. 51 – 100 D. 101 – 150E. 151 – 200 F. 201 – 250G. 251 – 300 H. 301 – 400I. > 400

Measures of Facebook Usage

Strongly Disagree

Disagree Agree

Strongly Agree

Facebook is part of my everyday activity

1 2 3 4

I am proud to tell people I’m on Facebook

1 2 3 4

Facebook has become part of my daily routine

1 2 3 4

I feel out of touch when I haven’t logged onto Facebook for a while

1 2 3 4

I feel I am part of the Facebook community

1 2 3 4

I would be sorry if Facebook shut down

1 2 3 4

Measures of Facebook Usage to Meet New People & Connect with Existing Offline Contacts

Strongly Disagree

Disagree Agree Strongly Agree

Off to OnlineI have used Facebook to check out someone I met socially

1 2 3 4

I use Facebook to learn more about other people in my class / workplace

1 2 3 4

I use Facebook to learn more about other people living near me

1 2 3 4

I use Facebook to keep in 1 2 3 4

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touch with my old friendsOn to OfflineI use Facebook to meet new people

1 2 3 4

Measures for Psychological Well-Being

Strongly Disagree

Disagree Agree Strongly Agree

Self-Esteem ScaleI feel that I’m a person of worth, at least on an equal plane with others

1 2 3 4

I feel that I have a number of good qualities

1 2 3 4

All in all, I am inclined to feel that I am a failure

1 2 3 4

I am able to do things as well as most other people

1 2 3 4

I feel I do not have much to be proud of

1 2 3 4

I take a positive attitude toward myself

1 2 3 4

On the whole, I am satisfied with myself

1 2 3 4

Satisfaction with Life ScaleIn most ways, my university / work life is close to my ideal

1 2 3 4

The conditions of my university / work life are excellent

1 2 3 4

I am satisfied with my university / work life

1 2 3 4

So far I have gotten the important things I want (university & work life)

1 2 3 4

If I could live my university life/ work life over, I would change almost nothing

1 2 3 4

Social Capital Scale

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Strongly Disagree

Disagree Agree

Strongly Agree

Bridging Social Capital ScaleI feel I am part of the community at work/university

1 2 3 4

I am interested in what goes on in my university/workplace

1 2 3 4

I would be willing to contribute to my university / workplace after graduation / outside of work hours

1 2 3 4

Interacting with different people in my university/workplace makes me want to try new things

1 2 3 4

Interacting with different people in my university/workplace makes me feel like a part of a larger community

1 2 3 4

I am willing to spend time to support general activities at work / university

1 2 3 4

I come into contact with new people all the time ( at work / in campus)

1 2 3 4

Interacting with people at work / university reminds me that everyone in the world is connected

1 2 3 4

Bonding Social Capital ScaleThere are several people at work / university I trust to solve my problems

1 2 3 4

If I needed any money for emergency purposes, I know someone at work / university I can turn to

1 2 3 4

There is someone at work / university I can turn to for advice about making important decisions

1 2 3 4

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The people I interact with would be good job references for me

1 2 3 4

I do not know people at work / university well enough to get them to do anything important

1 2 3 4

Appendix 2 - Journal

The Benefits of Facebook "Friends:" Social Capital and College Students' Use of Online Social Network Sites

Nicole B. EllisonCharles Steinfield

Cliff Lampe

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Department of Telecommunication, Information Studies, and Media Michigan State University

Abstract

This study examines the relationship between use of Facebook, a popular online social network

site, and the formation and maintenance of social capital. In addition to assessing bonding and

bridging social capital, we explore a dimension of social capital that assesses one's ability to

stay connected with members of a previously inhabited community, which we call maintained

social capital. Regression analyses conducted on results from a survey of undergraduate

students (N=286) suggest a strong association between use of Facebook and the three types of

social capital, with the strongest relationship being to bridging social capital. In addition,

Facebook usage was found to interact with measures of psychological well-being, suggesting

that it might provide greater benefits for users experiencing low self-esteem and low life

satisfaction.

Introduction

Social network sites (SNSs) such as such as Friendster, CyWorld, and MySpace allow

individuals to present themselves, articulate their social networks, and establish or

maintain connections with others. These sites can be oriented towards work-related

contexts (e.g., LinkedIn.com), romantic relationship initiation (the original goal of

Friendster.com), connecting those with shared interests such as music or politics (e.g.,

MySpace.com), or the college student population (the original incarnation of

Facebook.com). Participants may use the sites to interact with people they already know

offline or to meet new people. The online social network application analyzed in this

article, Facebook, enables its users to present themselves in an online profile,

accumulate "friends" who can post comments on each other's pages, and view each

other's profiles. Facebook members can also join virtual groups based on common

interests, see what classes they have in common, and learn each others' hobbies,

interests, musical tastes, and romantic relationship status through the profiles.

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Facebook constitutes a rich site for researchers interested in the affordances of social

networks due to its heavy usage patterns and technological capacities that bridge online

and offline connections. We believe that Facebook represents an understudied offline to

online trend in that it originally primarily served a geographically-bound community

(the campus). When data were collected for this study, membership was restricted to

people with a specific host institution email address, further tying offline networks to

online membership. In this sense, the original incarnation of Facebook was similar to

the wired Toronto neighborhood studied by Hampton and Wellman (e.g., Hampton,

2002; Hampton & Wellman, 2003), who suggest that information technology may

enhance place-based community and facilitate the generation of social capital.1 Previous

research suggests that Facebook users engage in "searching" for people with whom they

have an offline connection more than they "browse" for complete strangers to meet

(Lampe, Ellison, & Steinfield, 2006).

Online SNSs support both the maintenance of existing social ties and the formation of

new connections. Much of the early research on online communities assumed that

individuals using these systems would be connecting with others outside their pre-

existing social group or location, liberating them to form communities around shared

interests, as opposed to shared geography (Wellman, Salaff, Dimitrova, Garton, Gulia,

& Haythornthwaite, 1996). A hallmark of this early research is the presumption that

when online and offline social networks overlapped, the directionality was online to

offline—online connections resulted in face-to-face meetings. For instance, Parks and

Floyd (1996) report that one-third of their respondents later met their online

correspondents face-to-face. As they write, "These findings imply that relationships that

begin on line rarely stay there" (n.p.).

Although this early work acknowledged the ways in which offline and online networks

bled into one another, the assumed online to offline directionality may not apply to

today's SNSs that are structured both to articulate existing connections and enable the

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creation of new ones. However, because there is little empirical research that addresses

whether members use SNSs to maintain existing ties or to form new ones, the social

capital implications of these services are unknown.

An Overview of Facebook

Created in 2004, by 2007 Facebook was reported to have more than 21 million

registered members generating 1.6 billion page views each day (Needham & Company,

2007). The site is tightly integrated into the daily media practices of its users: The

typical user spends about 20 minutes a day on the site, and two-thirds of users log in at

least once a day (Cassidy, 2006; Needham & Company, 2007). Capitalizing on its

success among college students, Facebook launched a high school version in early

September 2005. In 2006, the company introduced communities for commercial

organizations; as of November 2006, almost 22,000 organizations had Facebook

directories (Smith, 2006). In 2006, Facebook was used at over 2,000 United States

colleges and was the seventh most popular site on the World Wide Web with respect to

total page views (Cassidy, 2006).

Much of the existing academic research on Facebook has focused on identity

presentation and privacy concerns (e.g., Gross & Acquisti, 2005; Stutzman, 2006).

Looking at the amount of information Facebook participants provide about themselves,

the relatively open nature of the information, and the lack of privacy controls enacted

by the users, Gross and Acquisti (2005) argue that users may be putting themselves at

risk both offline (e.g., stalking) and online (e.g., identify theft). Other recent Facebook

research examines student perceptions of instructor presence and self-disclosure (Hewitt

& Forte, 2006; Mazer, Murphy, & Simonds, 2007), temporal patterns of use (Golder,

Wilkinson, & Huberman, 2007), and the relationship between profile structure and

friendship articulation (Lampe, Ellison, & Steinfield, 2007).

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In contrast to popular press coverage which has primarily focused on negative outcomes

of Facebook use stemming from users’ misconceptions about the nature of their online

audience, we are interested in situations in which the intended audience for the profile

(such as well-meaning peers and friends) and the actual audience are aligned. We use

Facebook as a research context in order to determine whether offline social capital can

be generated by online tools. The results of our study show that Facebook use among

college-age respondents was significantly associated with measures of social capital.

Literature Review

Social Capital: Online and Offline

Social capital broadly refers to the resources accumulated through the relationships

among people (Coleman, 1988). Social capital is an elastic term with a variety of

definitions in multiple fields (Adler & Kwon, 2002), conceived of as both a cause and

an effect (Resnick, 2001; Williams, 2006). Bourdieu and Wacquant (1992) define social

capital as "the sum of the resources, actual or virtual, that accrue to an individual or a

group by virtue of possessing a durable network of more or less institutionalized

relationships of mutual acquaintance and recognition" (p. 14). The resources from these

relationships can differ in form and function based on the relationships themselves.

Social capital has been linked to a variety of positive social outcomes, such as better

public health, lower crime rates, and more efficient financial markets (Adler & Kwon,

2002). According to several measures of social capital, this important resource has been

declining in the U.S. for the past several years (Putnam, 2000). When social capital

declines, a community experiences increased social disorder, reduced participation in

civic activities, and potentially more distrust among community members. Greater

social capital increases commitment to a community and the ability to mobilize

collective actions, among other benefits. Social capital may also be used for negative

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purposes, but in general social capital is seen as a positive effect of interaction among

participants in a social network (Helliwell & Putnam, 2004).

For individuals, social capital allows a person to draw on resources from other members

of the networks to which he or she belongs. These resources can take the form of useful

information, personal relationships, or the capacity to organize groups (Paxton, 1999).

Access to individuals outside one's close circle provides access to non-redundant

information, resulting in benefits such as employment connections (Granovetter, 1973).

Moreover, social capital researchers have found that various forms of social capital,

including ties with friends and neighbors, are related to indices of psychological well-

being, such as self esteem and satisfaction with life (Bargh & McKenna, 2004;

Helliwell & Putnam, 2004).

Putnam (2000) distinguishes between bridging and bonding social capital. The former is

linked to what network researchers refer to as "weak ties," which are loose connections

between individuals who may provide useful information or new perspectives for one

another but typically not emotional support (Granovetter, 1982). Alternatively, bonding

social capital is found between individuals in tightly-knit, emotionally close

relationships, such as family and close friends. After briefly describing the extant

literature on these two forms of social capital and the Internet, we introduce an

additional dimension of social capital that speaks to the ability to maintain valuable

connections as one progresses through life changes. This concept, "maintained social

capital," permits us to explore whether online network tools enable individuals to keep

in touch with a social network after physically disconnecting from it.

Social Capital and the Internet

The Internet has been linked both to increases and decreases in social capital. Nie

(2001), for example, argued that Internet use detracts from face-to-face time with

others, which might diminish an individual's social capital. However, this perspective

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has received strong criticism (Bargh & McKenna, 2004). Moreover, some researchers

have claimed that online interactions may supplement or replace in-person interactions,

mitigating any loss from time spent online (Wellman, Haase, Witte, & Hampton, 2001).

Indeed, studies of physical (e.g., geographical) communities supported by online

networks, such as the Netville community in Toronto or the Blacksburg Electronic

Village, have concluded that computer-mediated interactions have had positive effects

on community interaction, involvement, and social capital (Hampton & Wellman, 2003;

Kavanaugh, Carroll, Rosson, Zin, & Reese, 2005).

Recently, researchers have emphasized the importance of Internet-based linkages for the

formation of weak ties, which serve as the foundation of bridging social capital.

Because online relationships may be supported by technologies like distribution lists,

photo directories, and search capabilities (Resnick, 2001), it is possible that new forms

of social capital and relationship building will occur in online social network sites.

Bridging social capital might be augmented by such sites, which support loose social

ties, allowing users to create and maintain larger, diffuse networks of relationships from

which they could potentially draw resources (Donath & boyd, 2004; Resnick, 2001;

Wellman et al., 2001). Donath and boyd (2004) hypothesize that SNSs could greatly

increase the weak ties one could form and maintain, because the technology is well-

suited to maintaining such ties cheaply and easily.

Based on this prior work, we propose the following hypothesis:

H1: Intensity of Facebook use will be positively associated with

individuals' perceived bridging social capital.

In Putnam's (2000) view, bonding social capital reflects strong ties with family and

close friends, who might be in a position to provide emotional support or access to

scarce resources. Williams (2006) points out that little empirical work has explicitly

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examined the effects of the Internet on bonding social capital, although some studies

have questioned whether the Internet supplements or supplants strong ties (see Bargh &

McKenna, 2004, for a review). It is clear that the Internet facilitates new connections, in

that it provides people with an alternative way to connect with others who share their

interests or relational goals (Ellison, Heino, & Gibbs, 2006; Horrigan, 2002; Parks &

Floyd, 1996). These new connections may result in an increase in social capital; for

instance, a 2006 Pew Internet survey reports that online users are more likely to have a

larger network of close ties than non-Internet users, and that Internet users are more

likely than non-users to receive help from core network members (Boase, Horrigan,

Wellman, & Rainie, 2006). However, it is unclear how social capital formation occurs

when online and offline connections are closely coupled, as with Facebook. Williams

(2006) argues that although researchers have examined potential losses of social capital

in offline communities due to increased Internet use, they have not adequately explored

online gains that might compensate for this. We thus propose a second hypothesis on

the relationship between Facebook use and close ties:


individuals' perceived bonding social capital.

Online social network tools may be of particular utility for individuals who otherwise

have difficulties forming and maintaining both strong and weak ties. Some research has

shown, for example, that the Internet might help individuals with low psychological

well-being due to few ties to friends and neighbors (Bargh & McKenna, 2004). Some

forms of computer-mediated communication can lower barriers to interaction and

encourage more self-disclosure (Bargh, McKenna, & Fitzsimons, 2002; Tidwell &

Walther, 2002); hence, these tools may enable connections and interactions that would

not otherwise occur. For this reason, we explore whether the relationship between

Facebook use and social capital is different for individuals with varying degrees of self-

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esteem (Rosenberg, 1989) and satisfaction with life (Diener, Suh, & Oishi, 1997; Pavot

& Diener, 1993), two well-known and validated measures of subjective well-being. This

leads to the two following pairs of hypotheses:

H3a: The relationship between intensity of Facebook use and bridging

social capital will vary depending on the degree of a person's self

esteem.

H3b: The relationship between intensity of Facebook use and bridging

social capital will vary depending on the degree of a person's

satisfaction with life.

H4a: The relationship between intensity of Facebook use and bonding

social capital will vary depending on the degree of a person's self

esteem.

H4b: The relationship between intensity of Facebook use and bonding

social capital will vary depending on the degree of a person's

satisfaction with life.

Maintained Social Capital and Life Changes

Social networks change over time as relationships are formed or abandoned.

Particularly significant changes in social networks may affect one's social capital, as

when a person moves from the geographic location in which their network was formed

and thus loses access to those social resources. Putnam (2000) argues that one of the

possible causes of decreased social capital in the U.S. is the increase in families moving

for job reasons; other research has explored the role of the Internet in these transitions

(Cummings, Lee, & Kraut, 2006; Wellman et al., 2001). Wellman et al. (2001), for

example, find that heavy Internet users rely on email to maintain long distance

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relationships, rather than using it as a substitute for offline interactions with those living

nearby.

Some researchers have coined the term "friendsickness" to refer to the distress caused

by the loss of connection to old friends when a young person moves away to college

(Paul & Brier, 2001). Internet technologies feature prominently in a study of

communication technology use by this population by Cummings, Lee, and Kraut

(2006), who found that services like email and instant messaging help college students

remain close to their high school friends after they leave home for college. We therefore

introduce a measure focusing specifically on the maintenance of existing social capital

after this major life change experienced by college students, focusing on their ability to

leverage and maintain social connections from high school.

Young adults moving to college need to create new networks at college. However, they

often leave friends from high school with whom they may have established rich

networks; completely abandoning these high school networks would mean a loss of

social capital. Granovetter (1973, 1982) has suggested that weak ties provide more

benefit when the weak tie is not associated with stronger ties, as may be the case for

maintained high school relationships. To test the role of maintained high school

relationships as weak, bridging ties, we adapted questions about general bridging

relationships, such as those in Williams (2006), to be specific to maintained

relationships with high school acquaintances as opposed to close friends. We call this

concept "maintained social capital." In keeping with the thrust of our prior hypotheses

about the role of Facebook and bridging social capital, we propose the following:


individuals' perceived maintained social capital.

Methods

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A random sample of 800 Michigan State University (MSU) undergraduate students was

retrieved from the MSU registrar's office. All 800 students were sent an email invitation

from one of the authors, with a short description of the study, information about

confidentiality and incentives, and a link to the survey. Two reminder emails were sent

to those who had not responded. Participants were compensated with a $5 credit to their

on-campus spending accounts. The survey was hosted on Zoomerang

(http://www.zoomerang.com), an online survey hosting site, and was fielded in April

2006. Only undergraduate users were included in our sampling frame. A total of 286

students completed the online survey, yielding a response rate of 35.8% (see Table 1 for

sample demographics). Demographic information about non-responders was not

available; therefore we do not know whether a bias existed in regards to survey

participation. However, when we compare the demographics of our sample to

information we have about the MSU undergraduate population as a whole, our sample

appears to be representative with a few exceptions. Female, younger, in-state, and on-

campus students were slightly overrepresented in our sample.2

Mean or % (N)

S.D.

Gender

male 34% (98)

female 66% (188)

Age 20.1 1.64

Ethnicity

white 87% (247)

non-white 13% (36)

Income1 3.18 2.04

Year in school2 2.55 1.07

Home residence

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in-state 91% (259)

out-of-state 09% (25)

Local residence

on campus 55% (157)

off campus 45% (127)

Member of fraternity/sorotity

08% (23) 1.01

Hours of Internet use per day3

2 hr, 56 min 1.52

Facebook members 94% (268)Table 1. Sample demographics (N=286)Notes: 1 represents household income; 1=under $20,000, 2=$20,000-$34,999, 3=$35,000-$49,999, 4=$50,000-$74,999, 5=$75,000 or more; 2 1=first year, 2=sophomore, 3=junior, 4=senior; 3 converted from ordinal scale using mid-point of response category (e.g., 1-2 hours=1 hour 30 minutes)

Measures

Our instrument included four broad types of measures, which are discussed in more

detail below. We collected information about demographic and other descriptive

variables, including gender, age, year in school, local vs. home residence, ethnicity, a

measure of Internet use adapted from LaRose, Lai, Lange, Love, and Wu (2005), and

whether respondents were Facebook members or not. (These items are reflected in

Table 1 above.) We also included Facebook usage measures, such as time spent using

Facebook and items designed to assess whether Facebook was used to meet new people

or to establish an online connection to pre-existing connections. Our instrument also

included measures of subjective well-being and as well as three social capital measures,

which served as our dependent variables.

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Measures of Facebook Usage

Facebook Intensity

The Facebook intensity scale (Cronbach's alpha=.83) was created in order to obtain a

better measure of Facebook usage than frequency or duration indices. This measure

includes two self-reported assessments of Facebook behavior, designed to measure the

extent to which the participant was actively engaged in Facebook activities: the number

of Facebook "friends" and the amount of time spent on Facebook on a typical day. This

measure also includes a series of Likert-scale attitudinal questions designed to tap the

extent to which the participant was emotionally connected to Facebook and the extent to

which Facebook was integrated into her daily activities (see Table 2 for item wording

and descriptive statistics).

Individual Items and Scale Mean S.D.

Facebook intensity1, 2 (Cronbach's alpha=0.83)

-0.08 0.79

About how many total Facebook friends do you have at MSU or elsewhere? 0=10 or less, 1=11-50, 2=51-100, 3=101-150, 4=151-200, 5=201-250, 6=251-300, 7=301-400, 8=more than 400

4.39 2.12

In the past week, on average, approximately how many minutes per day have you spent on Facebook? 0=less than 10, 1=10-30, 2=31-60, 3=1-2 hours, 4=2-3 hours, 5=more than 3 hours

1.07 1.16

Facebook is part of my everyday activity 3.12 1.26

I am proud to tell people I'm on Facebook 3.24 0.89

Facebook has become part of my daily routine 2.96 1.32

I feel out of touch when I haven't logged onto Facebook 2.29 1.20

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for a while

I feel I am part of the Facebook community 3.30 1.01

I would be sorry if Facebook shut down 3.45 1.14Table 2. Summary statistics for Facebook intensityNotes: 1 Individual items were first standardized before taking an average to create scale due to differing item scale ranges. 2 Unless provided, response categories ranged from 1=strongly disagree to 5=strongly agree.

Facebook Usage: Elements in Profile and Perceptions of Who Has Viewed Profiles

We asked respondents to indicate which of several salient aspects of the profile (such as

relationship status, high school, and mobile phone number) they included when

constructing their profile. The instrument asked respondents to indicate who they

thought had viewed their profile, such as high school friends, classmates, or family

members. These items offer insight into the degree to which respondents used Facebook

to maintain existing connections or meet new people.

Use of Facebook to Meet New People vs. Connect with Existing Offline Contacts

In order to further investigate whether usage was more motivated by prior offline

contacts or the potential to form new online contacts, we developed several items

reflecting each of these paths (see Table 3). In the former case, the items measured

whether respondents used Facebook to look up someone with whom they shared some

offline connection, such as a classmate or a friend (Cronbach's alpha=.70). In the latter

case, our instrument included several items that tapped the use of Facebook to make

new friends without any reference to an offline connection, but these did not correlate

highly, and our final analysis incorporated only a single item measure: using Facebook

to meet new people.

Individual Items and Scale1 Mean S.D.

Off to Online: I use Facebook to connect with offline 3.64 0.79

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contacts(Cronbach's alpha=0.70)

I have used Facebook to check out someone I met socially

3.99 1.05

I use Facebook to learn more about other people in my classes

3.26 1.20

I use Facebook to learn more about other people living near me

2.86 1.22

I use Facebook to keep in touch with my old friends 4.42 0.86

On to Offline: I use Facebook to meet new people (single item measure)

1.97 1.03

Table 3. Summary statistics for Facebook use for prior contacts and meeting new peopleNote: 1 Individual items ranged from 1=strongly disagree to 5=strongly agree, scales constructed by taking mean of items.

Measures for Psychological Well-Being

Self-Esteem

Self-esteem was measured using seven items from the Rosenberg self-esteem scale

(Rosenberg, 1989). The answers to these questions were reported on a 5-point Likert

scale and exhibited high reliability (see Table 4).

Satisfaction with Life at MSU

The scale of satisfaction with life at MSU was adapted from the Satisfaction with Life

Scale (SWLS) (Diener, Suh, & Oishi, 1997; Pavot & Diener, 1993), a five-item

instrument designed to measure global cognitive judgments of one's life. We amended

each item slightly to refer specifically to the MSU context, on the assumption that

restricting participants was more appropriate given our hypotheses and more likely to

elicit accurate answers. The reliability test for this 5-point Likert scale showed a

relatively high reliability (see Table 4).

Individual Items and Scale1 Mean S.D.

Self Esteem Scale (Cronbach's alpha=0.87) 4.30 0.55

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I feel that I'm a person of worth, at least on an equal plane with others

4.50 0.60

I feel that I have a number of good qualities 4.54 0.57

All in all, I am inclined to feel that I am a failure (reversed)

4.27 0.86

I am able to do things as well as most other people 4.29 0.63

I feel I do not have much to be proud of (reversed) 4.26 0.89

I take a positive attitude toward myself 4.17 0.75

On the whole, I am satisfied with myself 4.07 0.84

Satisfaction with MSU Life Scale (Cronbach's alpha=0.87)

3.55 0.74

In most ways my life at MSU is close to my ideal 3.42 0.96

The conditions of my life at MSU are excellent 3.54 0.91

I am satisfied with my life at MSU 3.85 0.84

So far I have gotten the important things I want at MSU 3.74 0.81

If I could live my time at MSU over, I would change almost nothing

3.18 1.05

Table 4. Summary statistics and factor analysis results for self-esteem and satisfaction with MSU life itemsNote: 1 Individual items ranged from 1=strongly disagree to 5=strongly agree, scales constructed by taking mean of items.

Measures of Social Capital

Our three measures of social capital—bridging, bonding, and maintained social capital

—were created by adapting existing scales, with wording changed to reflect the context

of the study, and creating new items designed to capture Internet-specific social capital

(Quan-Haase & Wellman, 2004). The full set of social capital items was factor analyzed

to ensure that the items reflected three distinct dimensions (see Table 5).

Factor Loadings1

Individual Items and Mea S.D Bridging Maintained Bonding

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Scales2 n . Social Capital

Social Capital

Social Capital

Bridging Social Capital Scale (Cronbach's alpha=0.87)

3.81 0.53

I feel I am part of the MSU community

3.78 0.80

0.70 -0.24 0.13

I am interested in what goes on at MSU

3.98 0.64

0.73 -0.10 0.13

MSU is a good place to be 4.22 0.78

0.73 -0.12 0.18

I would be willing to contribute money to MSU after graduation

3.35 0.95

0.66 -0.04 0.13

Interacting with people at MSU makes me want to try new things

3.74 0.68

0.60 -0.04 0.15

Interacting with people at MSU makes me feel like a part of a larger community

3.81 0.68

0.72 -0.09 0.23

I am willing to spend time to support general MSU activities

3.70 0.77

0.76 -0.10 0.16

At MSU, I come into contact with new people all the time

4.05 0.69

0.54 -0.17 0.13

Interacting with people at MSU reminds me that everyone in the world is connected

3.65 0.88

0.60 -0.07 0.04

Bonding Social Capital Scale (Cronbach's alpha=0.75)

3.72 0.66

There are several people at MSU I trust to solve my problems

3.22 1.01

0.17 -0.07 0.60

If I needed an emergency loan of $100, I know someone at MSU I can turn

3.75 1.09

0.02 -0.18 0.76

123

to

There is someone at MSU I can turn to for advice about making very important decisions

3.98 0.85

0.27 -0.09 0.76

The people I interact with at MSU would be good job references for me

3.88 0.79

0.32 0.07 0.63

I do not know people at MSU well enough to get them to do anything important (reversed)

3.78 0.87

0.13 -0.23 0.61

Maintained Social Capital Scale (Cronbach's alpha=0.81)

3.77 0.67

I'd be able to find out about events in another town from a high school acquaintance living there

3.59 0.88

0.20 -0.58 0.05

If I needed to, I could ask a high school acquaintance to do a small favor for me

3.92 0.89

0.06 -0.86 0.18

I'd be able to stay with a high school acquaintance if traveling to a different city

3.85 0.94

-0.02 -0.85 0.15

I'd be able to find information about a job or internship from a high school acquaintance

3.58 0.89

0.11 -0.79 0.02

It would be easy to find people to invite to my high school reunion

3.90 0.88

0.29 -0.56 0.14

Table 5. Summary statistics and factor analysis results for social capital itemsNotes: 1 Principal components factor analysis with varimax rotation, explaining 53% of the variance.2 Individual items ranged from 1=strongly disagree to 5=strongly agree, scales constructed by taking mean of items.

Bridging Social Capital

124

This measure assessed the extent to which participants experienced bridging social

capital, which is believed to be better-suited for linking to external assets and for

information diffusion (Putnam, 2000). According to Williams (2006), "members of

weak-tie networks are thought to be outward looking and to include people from a

broad range of backgrounds. The social capital created by these networks generates

broader identities and generalized reciprocity" (n.p.). We therefore adapted five items

from Williams' (2006) bridging social capital subscale and created three additional

items intended to measure bridging social capital in the MSU context to create our

bridging social capital scale (Cronbach's alpha=.87). One item, "MSU is a good place to

be," was included because it loaded on the same factor and tapped into an outcome of

bridging social capital.

Bonding Social Capital

Bonding was assessed using five items from the bonding subscale of the Internet social

capital scales developed and validated by Williams (2006). Responses were reported on

a five-point Likert scale. These items were adapted to the MSU context (Cronbach's

alpha=.75).

Maintained Social Capital

This original scale was inspired by our pilot interviews,3 media coverage of Facebook,

and anecdotal evidence that suggested that keeping in touch with high school friends

was a primary use of Facebook. These items were adapted from traditional measures of

social capital which assess an individual's ability to mobilize support or action

(Cronbach's alpha=.81) but focus on the ability to get assistance from apreviously

inhabited community.

Findings

125

We first present some basic descriptive data to characterize Facebook users and uses

and provide insight into whether Facebook is used more to meet new people or to

maintain or strengthen relationships with offline connections. In a short period of time,

Facebook has garnered a very strong percentage of users on college campuses. In our

sample, 94% of the undergraduate students we surveyed were Facebook members. We

investigated whether members and non-members differed significantly along various

demographic characteristics, but we lacked confidence in these findings given the

extremely low number of non-Facebook users. The remainder of our analyses are based

only on data from Facebook members.

Facebook members report spending between 10 and 30 minutes on average using

Facebook each day and report having between 150 and 200 friends listed on their

profile (Table 2). From Table 3 we see that respondents also report significantly more

Facebook use involving people with whom they share an offline connection—either an

existing friend, a classmate, someone living near them, or someone they met socially

(mean=3.64)—than use involving meeting new people (mean=1.97) (t=26.14, p<.0001).

Further insight into Facebook usage patterns can be gleaned from Figures 1 and 2,

which show what elements respondents report including in their Facebook profile and

who they believe has seen their profiles, respectively. The fact that nearly all Facebook

users include their high school name in their profile (96%) suggests that maintaining

connections to former high school classmates is a strong motivation for using Facebook.

Not surprisingly, 97% report that high school friends had seen their profile. Ninety

percent or more also reported that other friends as well as people in their classes had

seen their profile, further suggesting an offline component to Facebook use.4

126

Figure 1. Self-reported elements in respondents' Facebook profiles

Figure 2. Perceived audience for respondents' Facebook profiles

127

As Figure 2 suggests, students view the primary audience for their profile to be people

with whom they share an offline connection. This is suggested as well by the responses

to items about how they use Facebook. Mean scores for the offline-to-online scale were

significantly higher than those for the single-item online-to-offline measure (p<.0001).

This suggests that students use Facebook primarily to maintain existing offline

relationships or to solidify what would otherwise be ephemeral, temporary

acquaintanceships. There was a slight tendency for newer students to use Facebook to

meet new people more than for juniors and seniors to do so (see Figure 3), but across all

four years in school, respondents reported greater use of Facebook for connecting with

existing offline contacts.

Figure 3. Offline-to-online vs. online-to-offline mean scores by year in school

In order to explore our research hypotheses regarding the relationship between

Facebook use and the various forms of social capital, we conducted regression analyses.

128

In each regression, we controlled for demographic, subjective well-being and Internet

use factors, in order to see if usage of Facebook accounted for variance in social capital

over and above these other independent variables.

To test Hypothesis 1, we first investigated the extent to which demographic factors,

psychological well-being measures, and general Internet use predicted the amount of

bridging social capital reported by students; the adjusted R2 for this model was .38. We

then entered the Facebook intensity variable, which raised the adjusted R2 to .43. An

additional pair of analyses further explored whether Facebook intensity interacted with

the self-esteem and satisfaction with MSU life scales (see Table 6). The key finding is

that, after first controlling for demographic factors, psychological well-being measures,

and general Internet use, the extent to which students used Facebook intensively still

contributed significantly (scaled beta5=.34, p<.0001), supporting Hypothesis 1.

Interestingly, general Internet use was not a significant predictor of bridging social

capital, suggesting that only certain kinds of uses of the Internet support the generation

and maintenance of bridging social capital. The significance of these variables did not

change when the interaction terms were added. We also explored whether gender and

year in school interacted with Facebook intensity, in order to see if gender or time at

MSU accounted for variation in the association between bridging social capital and

Facebook use. These interactions were not significant and are not included in the table.

Overall, our independent factors accounted for nearly half of the variance in bridging

social capital. The results suggest that Facebook is indeed implicated in students' efforts

to develop and maintain bridging social capital at college, although we cannot assess

causal direction. Few demographic factors matter, although white students are

somewhat more likely to have bridging social capital than non-white students (scaled

beta=.08, p<.05). Among the psychological measures, the extent of students' satisfaction

with life at MSU was strongly correlated with bridging social capital (scaled beta=.66,

p<.0001).

129

To explore Hypotheses 3a and 3b, the interaction between Facebook use and the

psychological measures was examined (Figures 4 and 5). Both hypotheses, which

predicted that the relationship between Facebook use and bridging social capital would

vary based upon the degree of self-esteem and satisfaction with life, are supported.

Students reporting low satisfaction and low self-esteem appeared to gain in bridging

social capital if they used Facebook more intensely, suggesting that the affordances of

the SNS might be especially helpful for these students.

Model 1: Control Factors, Facebook Intensity, and Facebook X Self-Esteem Interaction

Model 2: Control Factors, Facebook Intensity, and Facebook X Satisfaction with MSU Life Interaction

Independent Variables1

Scaled Beta2 p3 Scaled Beta p

Intercept 3.80 **** 3.85 ****

Gender: male -0.02 -0.03

Gender: female 0.02 0.03

Ethnicity: white 0.08 * 0.07

Ethnicity: nonwhite -0.08 * -0.07

Income 0.04 0.05

Year in school 0.00 0.01

State residence: in-state

-0.05 -0.07

State residence: out-of-state

0.05 0.07

Local residence: on campus

-0.04 -0.03

Local residence: off campus

0.04 0.03

Fraternity/sorority member

-0.01 -0.03

Not a member of fraternity/sorority

0.01 0.03

130

Hrs of Internet use per day

-0.03 -0.01

Self esteem 0.20 *** 0.22 ****

Satisfaction with MSU

0.66 **** 0.61 ****

Facebook (FB) intensity

0.34 **** 0.31 ****

Self-esteem by FB intensity4

-0.35 **

Satisfaction by FB intensity

-0.51 ***

N=269 F=18.83, **** Adj. R2=.44

F=19.92, **** Adj. R2=.46

Table 6. Regressions predicting the amount of bridging social capital from demographic, attitudinal, and Facebook variablesNotes: 1 Nominal factors expanded to all levels. 2 Continuous factors centered by mean, scaled by range/2. 3 * p<.05, ** p<.01, *** p<.001, **** p<.0001. 4 Only one interaction term was entered at a time in each regression.

Figure 4. Interaction of Facebook use intensity and satisfaction with MSU life on bridging social capital

131

Figure 5. Interaction of Facebook intensity and self-esteem on bridging social capital

As shown in Table 7, bonding social capital was also significantly predicted by the

intensity with which students used Facebook (scaled beta=.37, p<.001 in model 2).

Other factors that related to bonding social capital were ethnicity (being white, scaled

beta=.16, p<.01, model 2), year in school (scaled beta=.22, p<.01, model 2), living on

campus (scaled beta=.13, p<.01, model 2), self-esteem (scaled beta=.23, p<.01, model

2), and satisfaction with MSU life (scaled beta =.40, p<.001, model 2). General Internet

use was not a significant predictor of bonding social capital, and the interactions

between Facebook use and the two psychological measures were not significant. As in

the bridging social capital analysis, gender and year in school did not interact

significantly with Facebook use in predicting bonding social capital. The adjusted R2

for the control factors alone was .19; adding Facebook Intensity raised this statistic

to .22. Again, the same variables were significant when the interactions were added.

132

Overall, the included variables accounted for almost one quarter of the variance in

students' reported bonding social capital.





Intercept 3.73 **** 3.76 ****

Gender: male 0.07 0.06

Gender: female -0.07 -0.06

Ethnicity: white 0.17 ** 0.16 **

Ethnicity: nonwhite -0.17 ** -0.16 **

Income 0.07 0.07

Year in school 0.23 *** 0.23 ***


-0.09 -0.10


0.09 0.10


0.13 ** 0.14 **


-0.13 ** -0.14 **


-0.07 -0.08


0.07 0.08


-0.01 0.01

Self esteem 0.22 ** 0.24 **


0.40 *** 0.37 ***


0.37 **** 0.34 ***

133


-0.32


-0.26

N=269 F=7.60, **** Adj. R2=.23

F=7.48, **** Adj. R2=.22

Table 7. Regressions predicting the amount of bonding social capital from demographic, attitudinal, and Facebook variablesNotes: 1 Nominal factors expanded to all levels. 2 Continuous factors centered by mean, scaled by range/2. 3 * p<.05, ** p<.01, *** p<.001, **** p<.0001. 4 Only one interaction term was entered at a time in each regression.

Finally, entering only our control factors accounted for 13% of the variance in

maintained social capital (Table 8). Adding Facebook intensity raised the R2 to .17 and

revealed the same strong connection to Facebook intensity (scaled beta=.36, p<.001),

even after controlling for the number of years at college (and thus, away from high

school) and general Internet use. Interestingly, general Internet use was also a

significant predictor of maintained social capital (scaled beta=.26, p<.05), suggesting

that other Internet applications are useful in this case. Ethnicity (being white, scaled

beta=.23, p<.001) and self-esteem (scaled beta=.30, p<.001) were the other significant

variables in this regression. None of the interactions were significant. Together, the

independent variables accounted for 16% to 17% of the variance in the maintained

social capital measure.





Intercept 3.57 **** 3.60 ****

Gender: male -0.02 -0.02

Gender: female 0.02 0.02

Ethnicity: white 0.23 *** 0.23 ***

134

Ethnicity: nonwhite -0.23 *** -0.23 ***

Income 0.08 0.08

Year in school -0.09 -0.08


0.06 0.05


-0.06 -0.05


-0.06 -0.05


0.06 0.05


-0.02 -0.03


0.02 0.03


0.26 * 0.27 *

Self esteem 0.30 *** 0.31 ***


-0.02 -0.04


0.37 **** 0.36 ***


-0.11


-0.29

N=269 F=5.40, **** Adj. R2=.16

F=5.57, **** Adj. R2=.17

Table 8. Regressions predicting the amount of maintained social capital from demographic, attitudinal, and Facebook variablesNotes: 1 Nominal factors expanded to all levels. 2 Continuous factors centered by mean, scaled by range/2. 3 * p<.05, ** p<.01, *** p<.001, **** p<.0001. 4 Only one interaction term was entered at a time in each regression.

Discussion

135

Returning to our original research question, we can definitively state that there is a

positive relationship between certain kinds of Facebook use and the maintenance and

creation of social capital. Although we cannot say which precedes the other, Facebook

appears to play an important role in the process by which students form and maintain

social capital, with usage associated with all three kinds of social capital included in our

instrument.

Although representation of non-users is low in our sample, when we compare members

vs. nonmembers, we see no real difference in demographics, with the exception of class

year and age (which is strongly correlated with class year). This is most likely due to

the fact that Facebook is a relatively recent phenomenon, and we would expect senior

students to be less likely to join. The high penetration and lack of any systematic

difference between members and non-members suggests that Facebook has broad

appeal, does not exclude particular social groups, and has not had a noticeable effect on

participants' grades.

Our participants overwhelmingly used Facebook to keep in touch with old friends and

to maintain or intensify relationships characterized by some form of offline connection

such as dormitory proximity or a shared class. For many, Facebook provided a way to

keep in touch with high school friends and acquaintances. This was demonstrated

through the fact that the most commonly included information on users' profiles was

likely to be relevant for existing acquaintances trying to find them (e.g., their high

school) and that nearly all users felt that their high school friends had viewed their

profile, and through respondents' self-reported types of use (connecting with offline

contacts as opposed to meeting new people). This offline to online movement differs

from the patterns observed by early researchers examining computer-mediated

communication and virtual communities. Due to the structure of the site, which blocks

entry to those without a school email address and then places individuals into

136

communities based on that email address, Facebook serves a geographically-bound user

base.6

Our first dimension of social capital—bridging—assessed the extent to which

participants were integrated into the MSU community, their willingness to support the

community, and the extent to which these experiences broadened their social horizons

or worldview. Our findings suggest that certain kinds of Facebook use (articulated by

our Facebook intensity items) can help students accumulate and maintain bridging

social capital. This form of social capital—which is closely linked to the notion of

"weak ties"—seems well-suited to social software applications, as suggested by Donath

and boyd (2004), because it enables users to maintain such ties cheaply and easily.

Although more research is needed to understand the nature of this trend, we suspect that

Facebook serves to lower the barriers to participation so that students who might

otherwise shy away from initiating communication with or responding to others are

encouraged to do so through Facebook's affordances.

Participants' reports about who is viewing their profile provide insight into this

dynamic. As depicted in Figure 2, students report that the primary audiences for their

profiles are high school friends and people they know from an MSU context. This

implies that highly engaged users are using Facebook to crystallize relationships that

might otherwise remain ephemeral. Haythornthwaite (2005) discusses the implications

of media that "create latent tie connectivity among group members that provides the

technical means for activating weak ties" (p. 125). Latent ties are those social network

ties that are "technically possible but not activated socially" (p. 137). Facebook might

make it easier to convert latent ties into weak ties, in that the site provides personal

information about others, makes visible one's connections to a wide range of

individuals, and enables students to identify those who might be useful in some capacity

(such as the math major in a required calculus class), thus providing the motivation to

activate a latent tie. These weak ties may provide additional information and

137

opportunities, which are expressed as dimensions of bridging social capital that speak to

interaction with a wide range of people and the more tolerant perspective this might

encourage. Facebook seems well-suited to facilitate these experiences, in that detailed

profiles highlight both commonalities and differences among participants.

We also found an interaction between bridging social capital and subjective well-being

measures. For less intense Facebook users, students who reported low satisfaction with

MSU life also reported having much lower bridging social capital than those who used

Facebook more intensely. The same was true for self-esteem. Conversely, there was

little difference in bridging social capital among those who reported high satisfaction

with life at MSU and high self-esteem relative to Facebook use intensity. One

explanation consistent with these interaction effects is that Facebook use may be

helping to overcome barriers faced by students who have low satisfaction and low self-

esteem. Because bridging social capital provides benefits such as increased information

and opportunities, we suspect that participants who use Facebook in this way are able to

get more out of their college experience. The suggestion that Facebook use supports a

"poor get richer" hypothesis, as opposed to the "rich get richer" findings reported in

other contexts (Kraut, Kiesler, Boneva, Cummings, Helgeson, & Crawford, 2002), may

be of special interest to Internet researchers.

Bonding social capital was also predicted by high self-esteem, satisfaction with

university life, and intense Facebook use, although overall, the regression model

predicting bonding social capital accounted for less of the variation for this dependent

variable than for bridging social capital. However, Facebook appears to be much less

useful for maintaining or creating bonding social capital, as indicated by the fact that

the bonding model only accounted for 22% of the variance (versus 46% in the bridging

social capital models). We might expect Facebook usage to have less of an impact on

bonding than bridging social capital given the affordances of this service. It can lower

barriers to participation and therefore may encourage the formation of weak ties but not

138

necessarily create the close kinds of relationships that are associated with bonding

social capital. Yet the strong coefficient for Facebook intensity suggests that Facebook

use is important for bonding social capital as well. One explanation is that it may help

individuals to maintain pre-existing close relationships, just as it can be used as a low-

maintenance way to keep tabs on distant acquaintances. For instance, in our pilot

interviews, students discussed the "birthday" feature of Facebook, which prompted

them to send birthday greetings to friends with minimal effort.

Finally, Facebook intensity predicted increased levels of maintained social capital,

which assessed the extent to which participants could rely on high school acquaintances

to do small favors. For college students, many of whom have moved away for the first

time, the ability to stay in touch with these high school acquaintances may illustrate

most clearly the "strength of weak ties" outlined by Granovetter (1973, 1982). These

potentially useful connections may be valuable sources of new information and

resources. Additionally, the ability to stay in touch with these networks may offset

feelings of "friendsickness," the distress caused by the loss of old friends.

Limitations to this study include the fact that we examined only one community.

Because the college years are a unique developmental period in the life cycle and

because the MSU Facebook community is closely coupled with the geographically

bounded MSU community, we are not able to generalize these findings to other kinds of

communities or social network tools. It may be that the positive outcomes linked to

Facebook use discussed here are limited to this special case in which the offline

community is bounded spatially and to the unique nature of the undergraduate

experience. Future research could explore Facebook use in other contexts, such as

organizations and high schools. Because we used a one-time survey, we cannot

establish causality. Additionally, the extremely low incidence of non-members, non-

White, or international students in our sample hampered our ability to assess the effects

of Facebook membership on these groups. Finally, respondents may have misreported

139

behavioral or demographic information, as we used self-reported rather than direct

measures of Facebook use and other variables.

To address these concerns, future research should approach Facebook use and the

generation of social capital via multiple methodologies. Profile capture and analysis

would allow researchers to marry survey responses with direct behavioral measures.

Additionally, experimental interventions would support causal claims; these

interventions could be in the form of a survey, with pre- and post-test data collected

from the site itself. Collecting longitudinal data over a series of years, tracking

incoming first-year students and following them after they graduate, is also a necessary

next step.

Conclusions

Our empirical results contrast with the anecdotal evidence dominating the popular press.

Although there are clearly some image management problems experienced by students

as reported in the press, and the potential does exist for privacy abuses, our findings

demonstrate a robust connection between Facebook usage and indicators of social

capital, especially of the bridging type. Internet use alone did not predict social capital

accumulation, but intensive use of Facebook did.

The strong linkage between Facebook use and high school connections suggests how

SNSs help maintain relations as people move from one offline community to another. It

may facilitate the same when students graduate from college, with alumni keeping their

school email address and using Facebook to stay in touch with the college community.

Such connections could have strong payoffs in terms of jobs, internships, and other

opportunities. Colleges may want to explore ways to encourage this sort of usage.

Online social network sites may play a role different from that described in early

literature on virtual communities. Online interactions do not necessarily remove people

140

from their offline world but may indeed be used to support relationships and keep

people in contact, even when life changes move them away from each other. In addition

to helping student populations, this use of technology could support a variety of

populations, including professional researchers, neighborhood and community

members, employees of companies, or others who benefit from maintained ties.

Acknowledgments

The authors wish to thank Dean Chuck Salmon and the College of Communication Arts

and Sciences at Michigan State University for their generous support of this research.

Notes

1. "Netville" residents with broadband Internet connections and access to a local

online community discussion board were more likely to be involved with their

neighbors than were their non-wired peers: They recognized three times as many

and talked to twice as many (Hampton & Wellman, 2003).

2. Differences were as follows: 54% of the MSU student population is female vs.

66% of our respondents; 58% of MSU students live off-campus vs. 45% of our

respondents; 11% of MSU students are out of state vs. 9% of our respondents.

3. We interviewed one graduate and six undergraduate students about their

Facebook use; the data were used to inform survey construction and study

design.

4. We asked Facebook users whether or not they had set the privacy settings on

their accounts to control who viewed their profiles. More than two thirds (70%)

either did not know (suggesting that they left the default setting of all members

of the MSU network) or said that their profile was visible by the entire MSU

network. Only 13% limited access only to their friends, while the rest blocked

only certain individuals. Figure 2 does not take respondents' privacy settings into

account.

141

5. A scaled beta is similar to a standardized regression coefficient in that the

coefficients are adjusted so that they correspond to factors that are scaled to

have a mean of zero and range of two. This makes it easier to compare effect

sizes when factors have different scales.

6. In May of 2006, Facebook began establishing company sites and allowed

members to choose their networks. Nonetheless, college Facebook communities

remain defined by those who have a school email account.

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About the Authors

Nicole Ellison is an assistant professor in the Department of Telecommunication,

Information Studies, and Media at Michigan State University. Her research explores

issues of self-presentation, relationship development, and identity in online

environments such as weblogs, online dating sites, and social network sites.

Address: 403 Communication Arts and Sciences, East Lansing, MI 48824, USA

Charles Steinfield is Professor and Chair of the Department of Telecommunication,

Information Studies, and Media at Michigan State University. His research interests

include the uses of online social networks, individual and organizational collaboration

via ICT, and e-commerce.

Address: 409 Communication Arts and Sciences Building, East Lansing, MI 48824,

USA

Cliff Lampe is an assistant professor in the Department of Telecommunication,

Information Studies, and Media at Michigan State University. His research interests

include the social practices and architecture of online communities, online rating

systems, social software, and user-generated content.

Address: 419 Communication Arts and Sciences Building, East Lansing, MI 48824,

USA

147

Appendix 3 – SPSS RESULTS

DEMOGRAPHIC FREQUENCIES

Gender


Cumulative

Percent

Valid Male 98 49.0 49.0 49.0

Female 102 51.0 51.0 100.0

Total 200 100.0 100.0

148

Age


Cumulative

Percent

Valid <15 Yo 7 3.5 3.5 3.5

15-24 Yo 164 82.0 82.0 85.5

25-34 Yo 19 9.5 9.5 95.0

>34 Yo 10 5.0 5.0 100.0

Total 200 100.0 100.0

149

Last Education


Cumulative

Percent

Valid High School 106 53.0 53.0 53.0

Diploma 5 2.5 2.5 55.5

Undergraduate 81 40.5 40.5 96.0

Midle Shcool 8 4.0 4.0 100.0

Total 200 100.0 100.0

150

Current Occupation


Cumulative

Percent

Valid Student 135 67.5 67.5 67.5

Employed 48 24.0 24.0 91.5

Entrepreneur 11 5.5 5.5 97.0

Unemployed 6 3.0 3.0 100.0

Total 200 100.0 100.0

151

On average, how many hours do you spend on the Internet daily


Cumulative

Percent

Valid <1 Hour 7 3.5 3.5 3.5

1-2 Hours 39 19.5 19.5 23.0

2-3 Hours 45 22.5 22.5 45.5

>3 Hours 109 54.5 54.5 100.0

Total 200 100.0 100.0

152

MEASURES OF FACEBOOK USAGE TO MEET NEW PEOPLE & CONNECT WITH EXISTING OFFLINE

Statistics

Measures of

Facebook Usage

to Meet New

People &

Connect with

Existing Offline

Contacts [I have

used Facebook

to check out

someone I met

socially]

Measures of

Facebook Usage

to Meet New

People & Connect

with Existing

Offline Contacts [I

use Facebook to

learn more about

other people in my

class / workplace]

Measures of

Facebook Usage

to Meet New

People &

Connect with

Existing Offline

Contacts [I use

Facebook to

learn more about

other people

living near me]

Measures of

Facebook

Usage to Meet

New People &

Connect with

Existing Offline

Contacts [I use

Facebook to

keep in touch

with my old

friends]

Measures of

Facebook

Usage to Meet

New People &

Connect with

Existing Offline

Contacts [I use

Facebook to

meet new

people]

N Valid 200 200 200 200 200

Missing 0 0 0 0 0

Frequency Table

Measures of Facebook Usage to Meet New People & Connect with Existing Offline Contacts [I

have used Facebook to check out someone I met socially]



Disagree 19 9.5 9.5 14.0

Agree 132 66.0 66.0 80.0

Strongly Disagree 40 20.0 20.0 100.0

Total 200 100.0 100.0

153

Measures of Facebook Usage to Meet New People & Connect with Existing Offline Contacts [I use Facebook to learn more about other people in my class / workplace]



Disagree 32 16.0 16.0 18.0

Agree 120 60.0 60.0 78.0


Total 200 100.0 100.0

Measures of Facebook Usage to Meet New People & Connect with Existing Offline Contacts [I use Facebook to learn more about other people living near me]



Disagree 52 26.0 26.0 29.5

Agree 113 56.5 56.5 86.0


Total 200 100.0 100.0

Measures of Facebook Usage to Meet New People & Connect with Existing Offline Contacts [I use Facebook to keep in touch with my old friends]



Disagree 6 3.0 3.0 4.0

Agree 113 56.5 56.5 60.5


Total 200 100.0 100.0

154

Measures of Facebook Usage to Meet New People & Connect with Existing Offline Contacts [I use

Facebook to meet new people]



Disagree 83 41.5 41.5 64.5

Agree 54 27.0 27.0 91.5


Total 200 100.0 100.0

Pie Chart

155

156

157

VALIDITY TEST RESULT

IntensityItem-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's Alpha if

Item Deleted

Intensity1 13.9000 9.447 .824 .819

Intensity2 14.2500 10.168 .542 .866

Intensity3 13.9000 9.528 .729 .833

Intensity4 14.2900 9.232 .659 .847

Intensity5 14.1100 10.350 .576 .859

Intensity6 13.8500 9.354 .686 .841

Self Esteem


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Self-Esteem1 18.4700 7.074 .551 .758

Self-Esteem2 18.3950 7.074 .637 .746

Self-Esteem3 18.4800 7.527 .257 .820

Self-Esteem4 18.4900 7.136 .528 .762

Self-Esteem5 18.5100 7.025 .402 .790

Self-Esteem6 18.3600 6.694 .693 .732

Self-Esteem7 18.3850 6.308 .691 .727

158

Life Satisfaction


Scale Mean

if Item

Deleted

Scale

Variance if

Item Deleted

Corrected Item-

Total

Correlation

Cronbach's

Alpha if Item

Deleted






Bridging Social capital

159


Scale Mean if Item

Deleted

Scale Variance if

Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if

Item Deleted

Bridging1 21.6900 10.798 .772 .871

Bridging2 21.6350 11.972 .558 .890

Bridging3 21.8250 11.271 .538 .895

Bridging4 21.5750 11.190 .697 .878

Bridging5 21.6300 10.707 .778 .870

Bridging6 21.7200 10.866 .773 .871

Bridging7 21.7950 10.847 .639 .885

Bridging8 21.5900 11.097 .663 .881

Bonding Social Capital

RELIABILITY TEST

Reliability

Scale: ALL VARIABLES

160


Scale Mean if Item

Deleted

Scale Variance if

Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if

Item Deleted

Bonding1 11.9750 3.683 .726 .558

Bonding2 12.3250 3.929 .467 .666

Bonding3 11.9900 3.698 .731 .557

Bonding4 12.0650 4.222 .566 .631

Bonding5 12.1650 5.304 .036 .836

Case Processing Summary

N %


Excludeda 0 .0

Total 200 100.0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

.867 6


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Intensity1 13.9000 9.447 .824 .819

Intensity2 14.2500 10.168 .542 .866

Intensity3 13.9000 9.528 .729 .833

Intensity4 14.2900 9.232 .659 .847

Intensity5 14.1100 10.350 .576 .859

Intensity6 13.8500 9.354 .686 .841

Reliability


161


N %


Excludeda 0 .0

Total 200 100.0


procedure.


Cronbach's

Alpha N of Items

.790 7


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Self-Esteem1 18.4700 7.074 .551 .758

Self-Esteem2 18.3950 7.074 .637 .746

Self-Esteem3 18.4800 7.527 .257 .820

Self-Esteem4 18.4900 7.136 .528 .762

Self-Esteem5 18.5100 7.025 .402 .790

Self-Esteem6 18.3600 6.694 .693 .732

Self-Esteem7 18.3850 6.308 .691 .727

Reliability


162


N %


Excludeda 0 .0

Total 200 100.0


procedure.


Cronbach's

Alpha N of Items

.859 5


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted






Reliability


163


N %


Excludeda 0 .0

Total 200 100.0


procedure.


Cronbach's

Alpha N of Items

.894 8


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Bridging1 21.6900 10.798 .772 .871

Bridging2 21.6350 11.972 .558 .890

Bridging3 21.8250 11.271 .538 .895

Bridging4 21.5750 11.190 .697 .878

Bridging5 21.6300 10.707 .778 .870

Bridging6 21.7200 10.866 .773 .871

Bridging7 21.7950 10.847 .639 .885

Bridging8 21.5900 11.097 .663 .881

Reliability


164


N %


Excludeda 0 .0

Total 200 100.0


procedure.


Cronbach's

Alpha N of Items

.712 5


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Bonding1 11.9750 3.683 .726 .558

Bonding2 12.3250 3.929 .467 .666

Bonding3 11.9900 3.698 .731 .557

Bonding4 12.0650 4.222 .566 .631

Bonding5 12.1650 5.304 .036 .836

165

REGRESSIONVariables Entered/Removedb

Model

Variables Entered

Variables

Removed Method

dimension0




Model Summary

Model

R R Square

Adjusted R

Square Std. Error of the Estimate

dimension0

1 .532a .283 .280 .40077


ANOVAb

Model Sum of

Squares df Mean Square F Sig.

1 Regression 12.578 1 12.578 78.311 .000a

Residual 31.802 198 .161

Total 44.380 199



Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 1.947 .133 14.636 .000

Intensity .409 .046 .532 8.849 .000

166

Regression



dimension0




Model Summary

Model

R R Square

Adjusted

R Square

Std. Error of the

Estimate

dimension0

1 .366a .134 .129 .45993


ANOVAb

Model Sum of

Squares df

Mean

Square F Sig.

1 Regression 6.461 1 6.461 30.543 .000a

Residual 41.884 198 .212

Total 48.345 199



Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) 2.202 .153 14.419 .000

Intensity .293 .053 .366 5.527 .000

Regression

167



dimension0

1 Self-Esteem*Intensity, Intensitya . Enter



Model Summary


dimension0

1 .877a .770 .767 .22776


ANOVAb

Model Sum of

Squares df Mean Square F Sig.

1 Regression 34.161 2 17.081 329.275 .000a

Residual 10.219 197 .052

Total 44.380 199



Coefficientsa

Model


Standardized

Coefficients

t Sig.B

Std.

Error Beta

1 (Constant) 1.350 .081 16.644 .000

Intensity .066 .031 .086 2.110 .036

Self-

Esteem*Intensity

.163 .008 .828 20.398 .000

168

Regression



dimension0




Model Summary

Model

R R Square Adjusted R Square

Std. Error of the

Estimate

dimension0

1 .728a .530 .525 .32532


ANOVAb

Model

Sum of Squares df

Mean

Square F Sig.

1 Regression 23.531 2 11.765 111.168 .000a

Residual 20.849 197 .106

Total 44.380 199



Coefficientsa


Coefficients

Standardized

Coefficients

t Sig.B

Std.

Error Beta

1 (Constant) 1.482 .117 12.638 .000

Intensity .213 .042 .277 5.046 .000

169



dimension0



Life-

Satisfaction*Intensity

.109 .011 .559 10.173 .000

Regression



dimension0




Model Summary


dimension0

1 .613a .376 .370 .39134


ANOVAb


1 Regression 18.174 2 9.087 59.336 .000a

Residual 30.170 197 .153

Total 48.345 199



Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

170



dimension0



B Std. Error Beta

1 (Constant) 1.761 .139 12.642 .000

Intensity .040 .054 .050 .752 .453

Self-Esteem*Intensity .120 .014 .585 8.746 .000


Regression



dimension0




Model Summary

Model

R R Square Adjusted R Square

Std. Error of the

Estimate

dimension0

1 .856a .733 .730 .25610


ANOVAb

Model

Sum of Squares df

Mean

Square F Sig.

1 Regression 35.424 2 17.712 270.054 .000a

Residual 12.921 197 .066

171



dimension0



Total 48.345 199



Coefficientsa


Coefficients

Standardized

Coefficients

t Sig.B

Std.

Error Beta

1 (Constant) 1.445 .092 15.655 .000

Intensity -.026 .033 -.032 -.779 .437

Life-

Satisfaction*Intensity

.177 .008 .870 21.014 .000

CORRELATION

172

Correlations

Intensity

Bridging Social

Capital



N 200 200

Bridging Social Capital Pearson Correlation .532** 1


N 200 200


Correlations

Intensity

Bonding Social

Capital



N 200 200

Bonding Social Capital Pearson Correlation .366** 1


N 200 200


Appendix 4 – CV

Curriculum Vitae

173

Personal Details

Name : Mohit KhianiSex : MalePlace / Date of Birth : Jakarta, February 2nd 1991Contact Address : Jln. Agung Permai 1 Block C6 No: 6, Sunter

Agung, North Jakarta, IndonesiaLand Phone : 021-64714382Mobile Phone : 08179812115E-mail Address : [email protected] ,

[email protected]. [email protected]

Educational Background

2004 – 2009: Mahatma Gandhi School (The Board of Secondary Education Indian Schools Indonesia)Matriculation -- GCE O LevelsHigher secondary -- GCE A Levels

Awards received:

Subject topper in Computing (Grade 12) – Secured 92% Average

Silver card for average > 80% (Grade 10)

174

Others: Excellent written and verbal skills in English and Bahasa

Indonesia. Possess excellent interpersonal communication skills. Honest Able to work under pressure

EXTRACURRICULAR ACTIVITIES

Member of the CAS (Care and Share) club.

Participated in Inter-house Soccer competition at Gandhi Memorial School and achieved 1st place (2009).

Participated in Inter-house Table Tennis Competition -1st place Singles (Grade 11 & 12).

Participated in Inter-house Table Tennis Competition- 1st place Doubles (Grade 10).

Participated in Mahatma Gandhi School’s fundraising events (2007-2009)

Participated in Binus International Charity Day 2009

Experience

PREFECT (Student Committee) of Mahatma Gandhi School ( 2007-2009)

175

Accounting & Computing (IT) tutor (2008-2009). Nominated as BEST LO (Liaison officer) in E.Com 2009 Member of the Event Division in E.Com 2010 Member of the Student Activity (SA) in Binus

International Student Committee (BISC) (2009-2010) Head of Research & Development (R&D) Division in

Binus International Student Committee (BISC) (2010-2011)

Member of Property Division in Binus International Leadership Training V (BILT V)

Stage Manager and Liaison Officer in Welcoming University of Virginia (UVA)

Liaison Officer in Binus International Job Expo 2009 Member of Public Relation and Promotion division in

International Photography Competition (IPC) 2010 Person In Charge (PIC) and Participant of Fundraising

Management Training Seminar Liaison Officer in D’Abc 2010 Member of Transportation, Accommodation and

Logistics For ASEAN Regional Youth Leaders Conference (RYLC) 2010

Head of Transportation, Accommodation and Logistics For ASEAN Regional Youth Leaders Conference (RYLC) 2011

Committee of Binus International Ping Pong Competition 2010 as a member of Property Division

176

Committee of Binus International Musicology –Music Competition held by Student Committee

Coordinator of Buddy Coordinators (CBC) of Welcoming Days 2010

Interests

Sports & Other activities Reading, learning new things, meeting new

people/socializing.

177