Impact of Confirmation Bias on Competitive Information Spread in Social Networks

TL;DR

This paper models how confirmation bias influences the spread of competing information in social networks, revealing how innate opinions and network structure affect equilibrium outcomes.

Contribution

It formulates a zero-sum game capturing confirmation bias effects and characterizes the resulting Nash equilibrium's dependence on key parameters.

Findings

Confirmation bias shifts equilibrium towards the center for non-neutral innate opinions.

Equilibrium does not move towards the center for competitive information sources simultaneously.

Numerical examples validate the theoretical analysis.

Abstract

This paper investigates the impact of confirmation bias on competitive information spread in the cyber-social network that comprises individuals in a social network and competitive information sources in cyber layer. We formulate the problem as a zero-sum game, which admits a unique Nash equilibrium in pure strategies. We characterize the dependence of pure Nash equilibrium on the public's innate opinions, the social network topology, as well as the parameters of confirmation bias. We uncover that confirmation bias moves the equilibrium towards the center only when the innate opinions are not neutral, and this move does not occur for the competitive information sources simultaneously. Numerical examples in the context of well-known Krackhardt's advice network are provided to demonstrate the correctness of theoretical results.