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)

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National Bureau of Economic Research (NBER)

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Asuman E. Ozdaglar

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

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