Damage Spreading and Opinion Dynamics on Scale Free Networks

TL;DR

This paper investigates how small initial opinion changes can spread through agents in scale-free networks using the Krause-Hegselmann model, revealing thresholds for widespread influence and implications for election dynamics.

Contribution

It introduces an analysis of damage spreading in opinion dynamics on scale-free networks, identifying critical thresholds for influence propagation.

Findings

Damage spreads at low confidence bounds epsilon_d.

A critical epsilon_s exists where perturbations reach all agents.

Damage spreading transition occurs at a specific epsilon_d value.

Abstract

We study damage spreading among the opinions of a system of agents, subjected to the dynamics of the Krause-Hegselmann consensus model. The damage consists in a sharp change of the opinion of one or more agents in the initial random opinion configuration, supposedly due to some external factors and/or events. This may help to understand for instance under which conditions special shocking events or targeted propaganda are able to influence the results of elections. For agents lying on the nodes of a Barabasi-Albert network, there is a damage spreading transition at a low value epsilon_d of the confidence bound parameter. Interestingly, we find as well that there is some critical value epsilon_s above which the initial perturbation manages to propagate to all other agents.