Opinion Dynamics and Learning in Social Networks

62 Pages Posted: 25 Sep 2010

See all articles by Daron Acemoglu

Daron Acemoglu

Massachusetts Institute of Technology (MIT) - Department of Economics; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER)

Asuman E. Ozdaglar

Massachusetts Institute of Technology (MIT) - Department of Electrical Engineering and Computer Science

Date Written: August 30, 2010

Abstract

We provide an overview of recent research on belief and opinion dynamics in social networks. We discuss both Bayesian and non-Bayesian models of social learning and focus on the implications of the form of learning (e.g., Bayesian vs. non-Bayesian), the sources of information (e.g., observation vs. communication), and the structure of social networks in which individuals are situated on three key questions: (1) whether social learning will lead to consensus, i.e., to agreement among individuals starting with different views; (2) whether social learning will effectively aggregate dispersed information and thus weed out incorrect beliefs; (3) whether media sources, prominent agents, politicians and the state will be able to manipulate beliefs and spread misinformation in a society.

Keywords: Bayesian updating, consensus, disagreement, learning, misinformation, non-Bayesian models, rule of thumb behavior, social networks

JEL Classification: C72, D83

Suggested Citation

Acemoglu, Daron and Ozdaglar, Asuman E., Opinion Dynamics and Learning in Social Networks (August 30, 2010). MIT Department of Economics Working Paper No. 10-15. Available at SSRN: https://ssrn.com/abstract=1682248 or http://dx.doi.org/10.2139/ssrn.1682248

Daron Acemoglu (Contact Author)

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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Centre for Economic Policy Research (CEPR)

London
United Kingdom

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Asuman E. Ozdaglar

Massachusetts Institute of Technology (MIT) - Department of Electrical Engineering and Computer Science ( email )

50 Memorial Drive
Cambridge, MA 02139-4307
United States
617-324-0058 (Phone)

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