Evolution of Cultural Norms and Dynamics of Sociopolitical Change

IDSS PIs: Munther Dahleh, Daron Acemoglu, Fotini Christia, Munther Dahleh, Ali Jadbabaie, Asuman Ozdaglar
Co-PIs: Larry Blume (Cornell University), Matt Jackson (Stanford University), Michael Kearns (University of Pennsylvania), Jon Kleinberg (Cornell University), Jure Leskovec (Stanford University)

The recent events in the Arab world have made it clear that questions related to political change, cultural dynamics, and societal transformations are not only of first-order importance for social science, but are also central to developing a scientific approach to policy making and planning. While advances in traditional game theory, political economy, development economics and political science have enabled a posteriori analysis, understanding and predicting sociopolitical change requires a new set of tools and a multidisciplinary analytical framework. This Department of Defense Multi-Investigator University Research Initiative (MURI) project brings together a world-class team of researchers to address this challenge.

The project is focused on developing rigorous theory, modeling, and empirical analysis of patterns of communication, interaction, and learning in networked societies. The PIs have developed a framework to study collective action and collective decisions, including how local interactions among individuals and groups with different information, levels of prominence, and preferences results in the spread of information and actions. This effort also looks at how leadership and history impact the evolution of social norms, as well as the role of institutions and politics in sociopolitical change. By developing theories of cascade and contagion in conjunction with field surveys and experiments, IDSS PIs and their collaborators are investigating social and political changes in societies (such as Arab Spring events), using these theories and a wide range of datasets including those from online social networks such as Twitter, Facebook and LinkedIn, as well as communication data from Afghanistan, Iraq, and Yemen. Some results of their work so far include developing novel strategies for suppressing epidemic spreading in large-scale networks, and creating game theoretic models of collective decision, coordination, and collective action.

References and Related Content:

“An Efficient Curing Policy for Epidemics on Graphs” IEEE Transactions on Network Science and Engineering, July-Dec. 2014.

“Yemen Calling: Seven Things Cell Data Reveal About Life In the Republic”Foreign Affairs, July 2015.

Why Nations Fail – MIT Video, March 2012.

http://www.seas.upenn.edu/~aromuri – project website

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