GETTING CONNECTED: SOCIAL SCIENCE IN THE AGE OF NETWORKS CAPSTONE PRESENTATION

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GETTING CONNECTEDSOCIAL SCIENCE IN THE AGE OF
NETWORKSCAPSTONE PRESENTATION

• Presenters David Easley, Jon Kleinberg, Kathleen
  OConnor, Michael Macy, Dan HuttenlocherRest of
  the Team John Abowd, Larry Blume, Geri Gay,
  Jeffrey Prince, David StrangTeam 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 LabAdamic and Adar, 2005
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Social Science and Networks
Trade flows between countries
Structure and Power
Blume, Easley, KleinbergTardos, 2007
KrempelPlumper, 2003
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Cascades, the Spread of Rumors, the Reliability
of Information
Links between political blogs prior to 2004
election---AdamicGlance, 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)

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Micro-Foundations of Social Networks

• Systematic investigations into factors that
  influence peoples
• 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 peoples 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
James (beard)
Mark (UK)
Jill (pink)
Ben (glasses)
Mary(brown pants)
Emma (penguin)
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!
Thats amazing you know my Uncle Charlie!
A Chance Encounter in a Distant Land Leads to
Small Talk
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Six Degrees of Separation

• The planet is very large 6.5b!

Yet the world is small 6
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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(No Transcript)
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Solved by Watts Strogatz

• A few long-range ties
• Create shortcuts between otherwise distant nodes

• While preserving the clustering of a social
  network

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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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Weak Ties Are Key

• 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

• 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?

Sequence of signatures on e-mail chain letter
protesting the Iraq war, with 18,119 nodes,
median depth is 288.
Liben-Nowell Kleinberg 2008, Tracing
information flow on a global scale using Internet
chain-letter data, PNAS 1054633-38.
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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
A B C
Time 1
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Number and clustering of friends
A B C
Time 2
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Number and clustering of friends
A B C
Time 3
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Number and clustering of friends
A B C
Time 4
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Number and clustering of friends
A B C
Time 5
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Number and clustering of friends
A B C
Time 6
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Number and clustering of friends
A B C
Time 7
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Number and clustering of friends
A B C
Time 8
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Why is Clustering Important?

• Chain-letters and social movements seem to avoid
  taking shortcuts
• Its the mutual friends that seem to be key to
  growth of communities
• If disease and information can take shortcuts,
  why cant 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 113702-34

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Maybe Its 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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1000000
100000
Timesteps
100000
Simple contagion that requires adoption by 1
neighbor
10000
0 .1 .2 .3 .4
.5 .6 .7 .8 .9
1
(High Clustering)
(No Clustering)
Proportion of Random Ties
Random ties promote the spread of information
(lower is faster)
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10000000
Social contagion that requires adoption by 3
neighbors
Phase transition in the social fabric Contagion
can no longer spread
Social contagion that requires adoption by 2
neighbors
1000000
Timesteps
100000
Simple contagion that requires adoption by 1
neighbor
10000
0 .1 .2 .3 .4
.5 .6 .7 .8 .9
1
(High Clustering)
(No Clustering)
Proportion of Random Ties
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
• Whats 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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Whats 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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Whats 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