Effects of noise and confidence thresholds in nominal and metric Axelrod dynamics of social influence

TL;DR

This paper investigates how noise and confidence thresholds influence Axelrod's social influence model, revealing that thresholds mainly affect quantitative aspects, while noise and metric features significantly impact opinion dynamics.

Contribution

It provides a comprehensive analysis of the effects of noise and confidence thresholds on Axelrod's model, including both nominal and metric features, using simulations and mean-field equations.

Findings

Interaction thresholds do not change the phase structure.

External noise causes a crossover between ordered and disordered states.

Extremists can significantly influence opinion dynamics.

Abstract

We study the effects of bounded confidence thresholds and of interaction and external noise on Axelrod's model of social influence. Our study is based on a combination of numerical simulations and an integration of the mean-field Master equation describing the system in the thermodynamic limit. We find that interaction thresholds affect the system only quantitatively, but that they do not alter the basic phase structure. The known crossover between an ordered and a disordered state in finite systems subject to external noise persists in models with general confidence threshold. Interaction noise here facilitates the dynamics and reduces relaxation times. We also study Axelrod systems with metric features, and point out similarities and differences compared to models with nominal features. Metric features are used to demonstrate that a small group of extremists can have a significant impact on the opinion dynamics of a population of Axelrod agents.