MURI overview - SEAS - University of Pennsylvania

Report
W911NF-12-1-0509
ARO MURI: Evolution of Cultural
Norms and Dynamics of
Socio-Political Change
Ali Jadbabaie
University of Pennsylvania
The Team
Ali Jadbabaie (PI) Michael Kearns Daron Acemoglu Asu Ozdaglar Munzer Dahleh Fotini Christia
University of Pennsylvania
Matt Jackson Jure Leskovec
Stanford University
Massachusetts Institute of Technology
Jeff Shamma
Georgia Institute of
Technology
Jon Kleinberg
Larry Blume
Cornell University
Motivation and Overview
• Goal: create a research program that leads to understanding of social norms,
political change, cultural dynamics, societal stability with a multi-dicsiplinary
lens involving network science, systems theory, dynamics, Economics, Political
Economy, Computer Science
• Many of the central questions involve interactions among individuals and groups
with different identities
– Study of collective phenomena and collective decision making in networked setting
with domain specific knowledge
– Need more quantitative approaches, beyond descriptive
• Need theory, principled modeling, data analysis, lab experiments, and field
surveys
• Need to educate a new breed of computational social scientists and engineers
Why us?
• Our team literally wrote the book on the topic
Meme tracker
How Does it all come together?
Network
Science
Economics/
Political
Economy
Systems
Theory
Computer
Science
Experiments/
Field studies
Jadbabaie [S2,M2] Acemoglu[S1,P2]Ozdaglar[M2,M3] Kearns
Collective behavior,
Dynamics of
Game Theory,
social aggregation,
sociopolitical
Networks,
dynamics of cascades change, learning Cascades
Dahleh [C1,C2]
Jackson [S1,S2]
Blume [S3, M1]
[M2,P4]
Behavioral Field studies, large Networks, games
Experiments, randomized surveys algorithms,
from conflict zones Modeling cascades
contagion
Control, Decision Social and economic Econometrics of
networks, evolution social networks,
making, Global
networked games of social norms
Emergence of trust
Theory
• First principles
• Rigorous math
• Algorithms
• Proofs
Modeling
Data
Analysis
Christia [P2,P3] Kleinberg[M1,P2]
Leskovec [M2,P2]Shamma [C1,C2]
Social networks
data and
experiments
Lab
Experiments
Learning in games,
robustness,
evolutionary dynamics
Real-World
Surveys
• Economics
• Analysis of
• Stylized, Controlled • Extremely challenging!
•Political Science
social
• Clean, real-world • Randomized, large scale
•Empirical data
network data data
studies
• How to deal with • computationa
“no physics”
l
• Social science
Agenda for the day
09:00-09:30
09:30-10:00
[S3,M1]
10:00-10:30
10:30-11:00
11:00-11:30
11:30-12:00
Modeling and analysis of cascades and contagion Jon Kleinberg, Cornell [M2]
Evolutionary games and identification and modeling of social interaction Larry Blume, Cornell
Networked global games Munzer Dahleh, MIT [C2]
Coffee Break
Evolution of Social Norms Matt Jackson, Stanford [S1]
Field Experiments: Role of post-conflict development Fotini Christia, MIT [P2]
12:00-12:30 Empirical study of Social Interactions: Twitter data Jure Leskovec, Stanford [P3]
12:30-1:30 Lunch (served in Levine 307)
1:30- 2:00
2:00-2:30
2:30-3:00
3:00-3:30
Political Change, Societal stability and emergence of democracies, Daron Acemoglu, MIT [P1]
Fluctuations, Systemic risk and cascades in networks Asu Ozdaglar, MIT [M3]
Competitive Contagion and Behavioral experiments Michael Kearns, Penn [P4,M2]
Coffee Break
3:30-04:00 Influencing Social Evolutionary Dynamics Jeff Shamma, GeorgiaTech [C1]
4:00-4:30 Social Learning and belief aggregation Ali Jadbabaie, Penn [S2]
04:30-5:30 Discussion and Feedback

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