Usability & sociability in online communities: A framework for research &

practice

Jenny PreeceProf. & Chair of Information Systems

UMBC, Baltimore, MD 21250, USA

preece@umbc.edu

www.ifsm.umbc.edu/onlinecommunities

Overview

• Definitions

• Sociability & usability

• Research example

• Conclusions & future research

Definitions of online community• Technologists• Sociologists and anthropologists• Business entrepreneurs (e-commerce)

• Any virtual space where people come together to get or give information or support, to learn, to discuss, to be with others online.

• Online communities support communication between patients, professionals, students, citizens and nations

• Small or large, local, national, or international, virtual or physi-virtual.

My definition (Preece, 2000)

• People –make the community. Group dynamics, needs and roles shape the community.

• Purposes – people come together for a purpose(s).

• Policies – behavior is governed by group norms, rules and sometimes formal policies.

Software – supports and influences community activity.

Some numbers (10/2001)

• 52m US Internet users, 55% check health sites

• 230m unique MSN users per month

• 29m AOL users, 1 million more per month

• Over 104m ICQ users, millions now ‘texting’

• Over 91,500 UseNet groups

• 50,000 IBM employees, World Jam, June ‘01

• 100 -150 immersive CAVE environments

Overview

• Definitions

• Sociability & usability

• Research example

• Conclusions & future research

Sociability and Usability

• Sociability is concerned with social interaction. Communities with good sociability have unambiguous, supportive, social structures.

• Usability is concerned with human-computer interaction. Systems with good usability are consistent, controllable and predictable.

Sociability

• Purpose – provide a clear statement of purpose, brand name, symbol

• People – support different types of participants and participation, show presence when appropriate, keep participants interested

• Policies – guide behavior by providing and encouraging conventions, moderate with policies, support trust and security

Usability

Dialog & social interaction support –provide support for communication – icons, reduce typing, visualizations

Information design – distinguish between new & old content, different types of content

Navigation – support moving around the community, searching messages, moving between modules

Access – consider speed of connection, not everyone has most recent technology

Pillars of participatory community-centered development

Sociability

Purpose People Policies

Usability Dialog & social

interaction support Information design Navigation Access

Support sociability, design usability

• Should there be a registration policy?- Who can join? - What effect will it have on membership?

• Write message, design form- Interaction design- Layout - e.g. position & size of boxes etc.- Relationship with database

Norms & rulesPolicies

Usability: Community i.e. Conviviality Efficiency Effectiveness

Policies(Lewin, 1930s)i.e. Authoritarian Democratic Laissez-faire Anarchic

Purposei.e. goals

Communityi.e. Type of activity How much By whom Satisfaction

People

Functionsi.e. roles

Identity

Communication:(Bales, 1950s)i.e. Informational Social-emotional

Operations:(McGrath, 1984)i.e. Generate Choose Negotiate Execute

Community FrameworkCommunity Framework

ScaffoldS

Sociabilityi.e. On-topic Reciprocity Empathy Trust Identifiability Com. ground Privacy

Softwarei.e. Navigation Community Information

Signals terminationMany CSCW issues

1

3

2

1-3 scaffolds suggested

KEY

Usability: Individual

Infrastructurei.e. Media typeNetwork capacityComputer capacity

Communityi.e. Type Stage Size Culture

3

Scaffolds Examples

1 People - roles Visibility: individuals, groups, communitySearch: people with certain characteristics.Tools to support different roles.

Babble social translucent (Erickson et al.) Donath (2002) flower gardens. Pictures, caricatures, icons, web pages to support identity.

2 Purposes – communication – Informational, social-emotional

Meaningful name & description Identify: topics, expertise, communication type, who speaks & to whom.Support: dictionary, thesaurus, translation, etiquette, FAQs, common ground, empathy & trust support, to reduce typing.

Sack social network diagrams (2000). Phrases to support common ground (Zimmer). Palette of communicative symbols. Tools and spaces for conflict resolution.

3 Policies – authoritarian, democratic, laissez-faire, anarchic – norm/rules, policies

Make explicit: norms & rules Support: facilitation, moderatingDecision making: discussion support, votingScaling: large groups, private discussion

Some large systems such as Delphi, voting software (e.g. id-book.com) and governance (e.g. in Diversity University). Tools for moderators.

Overview

• Definitions

• Sociability & usability

• Research example

• Conclusions & future research

Research: Silent participants or lurkers (Blair Nonnecke, 2000)

12 indepth interviews - Reasons for not posting• Uncomfortable in public• Learning about the group• Building identify • Fear of persistent messages• Information overload• Not necessary to post• Personal characteristics (e.g., shyness)

• Group influences

Lurkers often feel part of a community

From a lurker ...

“Maybe it's a sign of my own mild discomfort around being a lurker, but I found it reassuring to recognize myself and my behavior within the continuum you describe, and to see lurking treated seriously, with both acceptance and respect. As a lurker, I'm used to observing from the sidelines and participating vicariously, and it's strangely gratifying to read an article that speaks directly to that experience. It's almost like suddenly feeling part of an (until-now) invisible community of lurkers.”

Lurking online – data logging• 12 weeks• Started with 135 original subscriptions• Ended with 109 DLs• Health 77, software 21 • 147,946 messages were transcribed into records

and imported into an SQL database.• 60,000 members

• 19,000 posters.

(Nonnecke, 2000; Nonnecke & Preece, Chi’2000)

Lurking in 77 health and 21 software support lists

DL type

softwarehealth

Lu

rkin

g (

% o

f m

em

be

rsh

ip)

100

80

60

40

20

0

Variation of lurking levels for cumulative posts over 3 months

Posting levels (cumulative posts in 12 weeks)

3210

Me

an

lurk

ers

(%

of

me

mb

ers

hip

) 100

90

80

70

60

50

40

30

softwareDLshealthDLs

% lurking in health & software groups

0102030405060708090

All

Hea

lth

Sof

twar

e

Low lurking when:- lists are small- traffic is high- messages are short- few single posters- ‘stars’ are present

(Nonnecke, 2000)

(Nonnecke & Preece, 2000)

Question Result from logging study

P3 How many lurkers are there? Fewer than expected: still high with anaverage of over 55% for all DLs (whendefined as 0 posts in 3 months).

R3a Does lurking in health and software-support DLsdiffer?

Yes: health-support groups have lowerlevels of lurking (45% vs. 82%).

R3b If lurking is defined as no posting, what happensto lurking levels when the definition is broadenedto include minimal levels of posting, e.g., 1post/month?

Lurking increases rapidly and then levelsoff as definition is broadened. Health-support groups maintain their lower levelsof lurking (75% vs. 97% for softwarewhen lurking is defined as 3 or fewerposts/3 months).

R3c Is there a relationship between lurking and thenumber of members in the DL?

Yes: smaller DLs have fewer lurkers.

R3d Is there a relationship between lurking and thetraffic level of the DL?

Yes: higher traffic means lower lurking.

R3e If posting is concentrated with a few posters, howdoes that affect lurking levels?

The greater the concentration, the less thelurking.

R3f Are short messages related to lower levels oflurking?

Yes: short messages are related to lowerlevels of lurking.

R3g If clumpiness is an indication of interaction, doesit necessarily follow that increased clump size isrelated to decreased lurking?

Yes: larger clumps are related to lowerlevels of lurking.

R3h Is there a relationship between the number ofsingleton posters and level of lurking?

Yes: as the number of singleton postersrises (and those who do not receive aresponse), so does the lurking.

Table 6.2: Overview of results ordered by question (From Blair Nonnecke’s thesis, 2000, SBU London)

Social presence in Babble(Erickson et al., Chi’99)

Criteria for success Usability

Speed of learning

Productivity

User satisfaction

Retention

Errors

SociabilityNo. participants

No. messages Reciprocity On-topic discussion Empathy Trust

Social satisfaction Lurking Uncivil behavior

Overview

• Definitions

• Sociability & usability

• Research example

• Conclusions & future research

Research• Community dynamics and the role of an online patient

support community in everyday life (Diane Maloney-Krichmar)

• Lurking and participation in 1000 online communities (Dorine Andrews, Blair Nonnecke, Greg Morton)

• Communicating trust using mobile devices – empathy & predicability (Heidi Feng, Jonathan Lazar)

• What makes online communities successful? Evaluation heuristics and metrics (Chadia Abras)

• Framework for online community development (Clarisse S. de Souza)

• Supporting lightweight communication in health support communities (Clarisse S. de Souza)

‘We shape our buildings, and afterwards our buildings shape us’

Winston Churchill

‘My experience of the world is that things left to themselves don’t get right’

T. H. Huxley

Web sites

www.ifsm.umbc.edu/onlinecommunities“Online Communities: Desinging Usability, supporting sociability”(2000)Jenny Preece, John Wiley &Sons

www.id-book.com“Interaction Design: Beyond HCI”(2002) J. Preece, Y. Rogers, H. Sharp, John Wiley & Sons

www.ifsm.umbc.edu/~preece

www.ifsm.umbc.edu/onlinecommunities

Id-book.com

Publications• Andrews, D. & Preece, J. (2001) A conceptual framework for demographic groups resistant

to online community interaction. Proc. HICSS-34 IEEE Computer Society, Maui, Hawaii.• Preece, J. & Ghozati, K. (2000) Experiencing empathy online. In R. Rice & J. Katz, The

Internet and Health communication: experience and expectations. Thousand Oaks: Sage• Nonnecke, B. & Preece, J. (2000) Counting the silent. ACM CHI’2000, Hague, 73-80.• Brown, J., van Dam, A., Earnshaw, R., Encarnacao, J., Guedj, R., Preece, J., Shneiderman,

B. & Vince, J. (1999). Human-centered computing, online communities and virtual environments. ACM Interactions, 6 (5).

• Lazar, J., Tsoa, R., & Preece, J. (1999). One foot in cyberspace and the other on the ground: A case study of analysis and design issues in a hybrid virtual and physical community. WebNet Journal: Internet Technologies, Applications and Issues, 1(3), 49-57.

• Nonnecke, B., & Preece., J. (2000). Persistence and lurkers: A pilot study. Proc. HICSS-33 IEEE Computer Society, Maui, Hawaii.

• Preece, J. (1998). Empathic communities: Reaching out across the Web. ACM Interactions 5 (2), 32-43.

• Preece, J. (1999). Empathic communities: Balancing emotional and factual communication. Interacting with Computers, 12, 63-77.

• Preece, J., & Ghozati, K. (1998). In search of empathy online: A review of 100 online communities. Proc. 1998 Association for Information Systems, Americas Conference, Baltimore, USA.

Additional material if time

Community Framework – SociabilityCommunity Framework – Sociability

Community type Stage Size Culturei.e. local, national

Sociability:i.e. On-topic Reciprocity Empathy Trust Identifiability Common ground Privacy

Community Framework – Usability

Individual context

Infrastructure Software

Media typeNetwork capacityComputer capacity

Navigation designCommunity designInformation design

Community context

ConvivialityEfficiencyEffectiveness

ConsistentControllablePredictableUniversal usability

Trustworthiness

• Is evidence of trustworthiness needed?What are the implications for:- social interaction?- privacy and security?

• How can trust be assessed & communicated?- what are the usability issues?

Social capital

‘A society characterized by general reciprocity is

more efficient than a distrustful society …’

Robert D. Putnam, Bowling Alone, 2000. P.21

Evaluating & measuring sociability

Purpose Number of messagesAmount of on-topic discussionLevel of interactivityDegree of reciprocityQuality of contributionSatisfaction with social interactions

People Number of participantsNumber different types

Policies Flaming and uncivil behaviorLevel of trustworthinessDegree of empathy

Cyber-balkanization

‘Internet enables us to confine our communication to precisely those people who share our interests and are like us. … Fragmentation and group polarization, are significant risks.’

Cass Sunstein, republic.com, 2001, p. 192

Research: Empathy

‘Knowing what another person is feeling, feeling what another person is feeling and responding compassionately to another person’

Levenson & Reuf, 1992

Analysis of 500 messages

0

5

10

15

20

25

30

35

40

45

Other Narrative Empathy Factual

Evaluating & measuring usabilityDialog & social interaction

Time to learn to read or send, move, etc. Number of messages. Time to do a task Satisfaction with dialog & interaction Amount remembered. Number of errors

Information design

Time to read & understand. Satisfaction with information design. Amount of information remembered. Number of misunderstandings

Navigation Time to learn to navigate application. Time to complete navigation task. Satisfaction with navigation. Amount remembered. Wrong paths, errors

Access Can the software be run/down loaded? Time to download. Response time. Satisfaction with access