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贝叶斯更新与确认偏差下的集体意见形成模型

Collective opinion formation model under Bayesian updating and confirmation bias.

作者信息

Nishi Ryosuke, Masuda Naoki

机构信息

National Institute of Informatics, 2-1-2 Hitotsubashi, Tokyo 101-8430, Japan.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Jun;87(6):062123. doi: 10.1103/PhysRevE.87.062123. Epub 2013 Jun 18.

Abstract

We propose a collective opinion formation model with a so-called confirmation bias. The confirmation bias is a psychological effect with which, in the context of opinion formation, an individual in favor of an opinion is prone to misperceive new incoming information as supporting the current belief of the individual. Our model modifies a Bayesian decision-making model for single individuals [M. Rabin and J. L. Schrag, Q. J. Econ. 114, 37 (1999)] for the case of a well-mixed population of interacting individuals in the absence of the external input. We numerically simulate the model to show that all the agents eventually agree on one of the two opinions only when the confirmation bias is weak. Otherwise, the stochastic population dynamics ends up creating a disagreement configuration (also called polarization), particularly for large system sizes. A strong confirmation bias allows various final disagreement configurations with different fractions of the individuals in favor of the opposite opinions.

摘要

我们提出了一个具有所谓确认偏差的群体意见形成模型。确认偏差是一种心理效应,在意见形成的背景下,支持某一意见的个体倾向于将新传入的信息错误地感知为支持其当前信念。我们的模型针对个体相互作用且充分混合的群体在无外部输入的情况下,对单一个体的贝叶斯决策模型[M. 拉宾和J. L. 施拉格,《经济学季刊》114卷,第37页(1999年)]进行了修正。我们对该模型进行了数值模拟,结果表明只有当确认偏差较弱时,所有个体最终才会在两种意见中达成一致。否则,随机的群体动态最终会导致出现分歧状态(也称为两极分化),特别是对于较大规模的系统。强烈的确认偏差会导致出现各种最终的分歧状态,其中支持相反意见的个体比例各不相同。

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