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GETTING CONNECTED:SOCIAL SCIENCE IN THE AGE OF NETWORKS
CAPSTONE PRESENTATION
Presenters: David Easley, Jon Kleinberg, Kathleen O’Connor, Michael Macy, Dan Huttenlocher
Rest of the Team: John Abowd, Larry Blume, Geri Gay, Jeffrey Prince, David Strang
Team Postdocs: Mary Still, Ted Welser
April 23, 2008
2
The Cornell Networks Team
From across Cornell: Arts & Sciences, CALS, CIS, ILR, Johnson School
3
What are Networks?
Transportation Network
4
Social Networks with Data Collected by Hand
Nodes-people, Edges-friendships
Friendships in a 34-person karate club that split apart---Zachary, 1977
5
Social Network Discovered from Traces of Online Data
Email communication between 436 employees in HP Research Lab—Adamic and Adar, 2005
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Social Science and Networks
Trade flows between countriesStructure and Power
Krempel+Plumper, 2003 Blume, Easley, Kleinberg+Tardos, 2007
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Cascades, the Spread of Rumors, the Reliability of Information
Links between political blogs prior to 2004 election---Adamic+Glance, 2005
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Networks are Everywhere
The study of networks integrates ideas from the social sciences and computer science, as well as information science, statistics, biology, physics…
The growth of the Internet has provided us with data that previously was difficult or impossible to obtain
Cornell is a leader in this area
9
Networks and the ISS
Encourage collaboration across disciplinary boundaries– Ongoing research between economists,
sociologists, psychologists, and computer and information scientists
Engage the Cornell community (faculty, graduate students and undergrads) in cutting-edge research– Post docs– Graduate students– New undergrad courses with large enrollment
10
Theme Project Activities
Workshops, seminars, reading groups
Educational initiatives
Funding and recruiting opportunities
New inter-disciplinary research directions
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Conferences
Ran conferences on aspects of project theme– “Search and Diffusion in Social Networks”
– “Symposium on Self-Organizing Online Communities” (co-sponsored by Microsoft)
Brought national leaders from academia and industry to campus– E.g., Ron Burt, Nosh Contractor, Paul Dimaggio, Matt
Jackson, Michael Kearns, Bob Kraut, Peter Monge, Duncan Watts, Barry Wellman …
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Educational Initiatives
New courses in all project areas, from introductory to graduate– Network material incorporated into existing
courses
– ECON, SOC, COMM, ILR, CIS, JGSM
“Networks”: new intro undergrad course– Cross-listed in ECON, SOC, CS, INFO
– This spring: 280 students from 33 different majors
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Networks(ECON/SOC/CS/INFO 204)
A course on how the social, natural, and technological worlds are connected, and how the study of networks shed light on these connections. Topics include: how opinions, fads, and political movements spread through society; the robustness and fragility of food webs and financial markets; and the technology, economics, and politics of Web information and on-line communities.
High-school dating (Bearman, Moody, & Stovel 2004)
Corporate e-mail (Adamic and Adar, 2005)
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Networks Class Blog
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Recruiting and Funding
Networks activity on campus enhanced many other efforts
Recruiting directions related to networks in Sociology, Communication, and CIS
Large-Scale NSF funding– Cyberinfrastructure tools (2005-present)– New proposals being pursued by expanded
version of project team
16
New Research Directions
Networks activity drew in many faculty beyond original project team
New research informed by perspectives from multiple areas
Next: two examples (out of many)– Social cognition and individual behavior– Social contagion and on-line communities
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Social Networks Represent Relationships Among People
People work collaboratively, share opinions, create new knowledge through their decisions to build a relationship (or not)
How do people understand and navigate their social environments to gain resources they care about—ideas, opinions, social support, political allies, status, for example? (Stephen Sauer and Ted Welser)
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Micro-Foundations of Social Networks
Systematic investigations into factors that influence people’s– Cognitions about their social networks
– Intentions to create relationships (ties)
– Efforts to create relationships
Goals– Understanding how networks evolve
– A psychological account of the spread of influence and ideas in social systems
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People and their Network Positions
Personality psychology perspective– People are endowed with traits that are
heritable, unaffected by external influences, and stable across the life span
Links between people’s traits and their positions in their social networks (Klein, Lim, Saltz, & Mayer, 2004)– People who are high in neuroticism tend to be
less central in their networks (advice and friendship)
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A Novel Social Network on Second Life
Mary(brown pants)
Ben (glasses)
Emma (penguin)
Jill (pink)
James (beard)
Mark (UK)
Scene from Second Life
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Where We Are Going
How do people understand and navigate their social environments to gain resources they care about?
Develop interventions to teach people strategies to make them more effective
– Better able to spot opportunities to build social capital
– Better able to translate those opportunities into advantageous network positions
New forms of social engagement and interaction give us new (and improved?) ways of studying social cognition and social behavior
22
It certainly is a small world!
A Chance Encounter in a Distant Land Leads to Small Talk…That’s amazing you know my Uncle Charlie!
23
Six Degrees of Separation
Yet the world is small: 6˚
The planet is very large: 6.5b!
How is this possible?
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Adding to the Mystery…
Easy to explain if the social ties were random
But friendships tend to be highly clustered
B
A
C
26
Solved by Watts & Strogatz
– While preserving the clustering of a social network
A few long-range ties– Create “shortcuts” between otherwise distant nodes
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The “Strength of Weak Ties”
Long-range ties tend to be relationally weak– Less frequent interaction
– Lower trust and influence
But structurally strong– Access to new ideas and information
– Accelerate the spread of disease
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“Whatever is to be diffused can reach a larger number of people, and traverse a greater social distance, when passed through weak ties rather than strong.”
-- Mark Granovetter, 1973
Weak Ties Are Key
A truism across the social & information sciences
But there are some intriguing anomalies...
29
The Chain-Letter Paradox*
If most people are separated by only six degrees, why are chain letters hundreds of links long?
*Liben-Nowell & Kleinberg 2008, “Tracing information flow on a global scale using Internet chain-letter data,” PNAS 105:4633-38.
Sequence of signatures on e-mail chain letter protesting the Iraq war, with 18,119 nodes, median depth is 288.
30
The Problem of “Critical Mass”
If an epidemic can quickly leap continents and reach millions of people in a few days, why do social movements often spread spatially and incrementally prior to reaching a “take-off” point?
31
Why Are Communities Clustered?
A cluster is a dense “cloud” of mutual friends
How do these form?– Conventional wisdom: people join communities
and then become mutual friends
– Maybe it is actually the other way around: people join communities to be with mutual friends?
32
Social Cloud Formation
875 LiveJournal (blogging) communities
Individuals one degree removed
Joining as a function of– Number of friends who are already members
– Clustering among friends
*Backstrom, Huttenlocher, Kleinberg, Lan, 2006. “Group Formation in Large Social Networks: Membership, Growth, & Evolution,” Proc. 12th ACM SIGKDD Intl. Conf. on Knowledge Discovery & Data Mining.
33
Number and clustering of friends
Time 1
A B C
34
Time 2
A B C
Number and clustering of friends
35
Time 3
A B C
Number and clustering of friends
36
Time 4
A B C
Number and clustering of friends
37
Time 5
A B C
Number and clustering of friends
38
Time 6
A B C
Number and clustering of friends
39
Time 7
A B C
Number and clustering of friends
40
Time 8
A B C
Number and clustering of friends
41
Why is Clustering Important?
Chain-letters and social movements seem to avoid taking “shortcuts”
It’s the mutual friends that seem to be key to growth of communities
If disease and information can take “shortcuts,” why can’t social contagions?
42
A Simple Explanation*
Social contagions differ from disease and information– Acquiring information is not the same thing as
acting on it• The same information from two friends is redundant
• The same advice from two friends is not
– Credibility, legitimacy & utility of adoption usually increase with the number of prior adopters
*Centola, D. and M. Macy. 2007. “Complex Contagions & the Weakness of Long Ties.” American Journal of Sociology 113:702-34
43
Maybe It’s Not Such a Small World After All?
Information and disease benefit from “weak ties” that create shortcuts– A single contact is sufficient for transmission
– Clustering is therefore redundant
Social contagions benefit from clustering– “Redundancy” provides social reinforcement
– Long-range ties inform but do not persuade
44
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
10000
100000
100000
1000000
Proportion of Random Ties
Tim
este
ps
Random ties promote the spread of information (lower is faster)
(High Clustering)
(NoClustering)
Simple contagion that requires adoption by 1 neighbor
45
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
10000
100000
1000000
10000000
Proportion of Random Ties
Tim
este
ps
Phase transition in the social fabric:Contagion can no longer spread
(High Clustering)
(NoClustering)
Simple contagion that requires adoption by 1 neighbor
Social contagion that requires adoption by 2 neighbors
Social contagion that requires adoption by 3 neighbors
But not the spread of social contagions
46
Small Worlds in a Bigger Picture
Social life is hard to observe
You can interview friends, but you cannot interview a friendship– Fleeting interaction
– In private
– Tedious to record over time, especially in large groups
47
Why This is Changing
Humans increasingly interact publicly online– Web pages, Facebook, blogs, wikis, games
– Computer-mediated interaction leaves digital traces
– New era of “connectionist” social science?• Interactions among people, not just variables
• Networks, not just aggregates of individuals
• Dynamics, not just comparative statics
• Links the talents & tools of social, computer, and information scientists
48
Some closing observations
What’s next
49
Observations
What does it mean to do interdisciplinary work with a dozen faculty across such broad range of fields?– Sociology, economics, communications, social
psychology, information science, computer science
More than joint projects across disciplinary boundaries – catalyst for research– Investigations deeply informed and motivated
by research of members in other fields – but published in established (disciplinary) venues
50
Observations
Importance of residential year, with lead-in and follow-up years– Build deeper ties and understanding across
disciplines through seminars, visitors, workshops, proposals, informal discussion
– Exposure to both classical literature and current work in several areas
Educational initiatives at both graduate and undergraduate level also engage team members in broader understanding– Research that happened as a result
51
Observations
Qualitative change in external visibility of Cornell in networks area– In both social sciences and computer science
– Had good basis for this in prior activities by various individuals – both on team and others
– Institutional commitment and increased activity level both important for the boost
Holding interdisciplinary workshops with the best people in the world – they leave impressed with Cornell
52
What’s Next
The team, plus a number of others, is planning to continue working together– The Information Science program provides a
natural inter-disciplinary venue for continued interaction
We are seeking large-scale external funding for this research– NSF CISE Expeditions proposal would be 5
years at $2M/yr
– Will pursue that program and others at similar scale
53
What’s Next
Build on the increased visibility and momentum in research activity– Long-term institutional impact
Best way we see to do this is coordinated faculty hiring in networks area– Joint appointments, or joint recruiting
committees for single department hires
54
We want to give our thanks to the ISS for supporting this project!
Thanks also to Microsoft for additional support of postdocs and workshops