Consensus in social networks: Revisited

Steven Kivinen and Norovsambuu Tumennasan ()

Journal of Mathematical Economics, 2019, vol. 83, issue C, 11-18

Abstract: We analyze the convergence of opinions or beliefs in a general social network with non-Bayesian agents. We provide a new sufficient condition under which opinions converge to consensus and the condition is significantly more permissive than that of Lorenz (2005). This condition, which depends on properties of the network, requires agents to incorporate others’ opinions into their own posterior sufficiently often.

Keywords: Networks; Consensus; Learning (search for similar items in EconPapers)
Date: 2019
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Working Paper: Consensus in Social Networks: Revisited (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:mateco:v:83:y:2019:i:c:p:11-18

DOI: 10.1016/j.jmateco.2019.03.006

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