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

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The Cornell Networks Team

From across Cornell: Arts & Sciences, CALS, CIS, ILR, Johnson School

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What are Networks?

Transportation Network

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Social Networks with Data Collected by Hand

Nodes-people, Edges-friendships

Friendships in a 34-person karate club that split apart---Zachary, 1977

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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

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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

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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

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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

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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!

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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

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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...

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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.

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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?

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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?

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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.

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Number and clustering of friends

Time 1

A B C

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Time 2

A B C

Number and clustering of friends

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Time 3

A B C

Number and clustering of friends

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Time 4

A B C

Number and clustering of friends

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Time 5

A B C

Number and clustering of friends

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Time 6

A B C

Number and clustering of friends

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Time 7

A B C

Number and clustering of friends

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Time 8

A B C

Number and clustering of friends

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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?

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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

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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

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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

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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

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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

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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

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Some closing observations

What’s next

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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

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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

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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

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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

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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

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We want to give our thanks to the ISS for supporting this project!

Thanks also to Microsoft for additional support of postdocs and workshops