A collective opinion formation model under Bayesian updating and confirmation bias

TL;DR

This paper introduces a collective opinion formation model incorporating confirmation bias, demonstrating how varying bias strength influences consensus or polarization in a population through numerical simulations.

Contribution

It extends Bayesian opinion models by integrating confirmation bias, revealing its impact on consensus formation and polarization in social dynamics.

Findings

Weak confirmation bias leads to consensus.

Strong confirmation bias results in polarization.

Larger populations tend to polarize more under strong 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.