Opinion Dynamics and Learning in Social Networks
Name
Acemoglu10-15.pdf
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382.43 KB
Format
Adobe PDF
Checksum (MD5)
e4b80c207578a13725c09cd30e053e4c
Author(s)
Acemoglu, Daron
Ozdaglar, Asuman
Date Issued
August 30, 2012
Publisher
Cambridge, MA: Department of Economics, Massachusetts Institute of Technology
Series/Report no.
Working paper, Massachusetts Institute of Technology, Dept. of Economics;10-15
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.
Subjects
Bayesian updating
consensus
disagreement
learning
misinformation
non-Bayesian Models
rule of thumb behavior
social networks
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