title: Collective opinion formation model under Bayesian updating and confirmation bias.
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.
authors.affiliation: National Institute of Informatics, 2-1-2 Hitotsubashi, Tokyo 101-8430, Japan.
authors.forename: Ryosuke
authors.initials: R
authors.lastname: Nishi
authors.forename: Naoki
authors.initials: N
authors.lastname: Masuda
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003198:Computer Simulation; D005716:Game Theory; D006801:Humans; D008960:Models, Psychological; D010363:Pattern Recognition, Automated / Q000379:methods*; D011639:Public Opinion