Opinion Dynamics with Bayesian Learning

Aili Fang, Kehua Yuan, Jinhua Geng and Xinjiang Wei

Complexity, 2020, vol. 2020, 1-5

Abstract:

Bayesian learning is a rational and effective strategy in the opinion dynamic process. In this paper, we theoretically prove that individual Bayesian learning can realize asymptotic learning and we test it by simulations on the Zachary network. Then, we propose a Bayesian social learning model with signal update strategy and apply the model on the Zachary network to observe opinion dynamics. Finally, we contrast the two learning strategies and find that Bayesian social learning can lead to asymptotic learning more faster than individual Bayesian learning.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8261392

DOI: 10.1155/2020/8261392

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