Social Influence and Consensus Building: Introducing a q-Voter Model with Weighted Influence

TL;DR

This paper introduces a weighted q-voter model for opinion dynamics, revealing how bias influences consensus formation, steady states, and critical slowing down, with results applicable to both small and large groups.

Contribution

The study extends the q-voter model by incorporating a bias parameter, analyzing its effects on opinion consensus and identifying universal behaviors and critical thresholds.

Findings

Bias determines the final opinion consensus in large systems.

Near neutral bias, the system exhibits critical slowing down.

Consensus time scales logarithmically or linearly depending on bias.

Abstract

We investigate a dynamical model of opinion formation in which an individual's opinion is influenced by interactions with a group of other agents. We introduce a bias towards one of the opinions in a manner not considered earlier to the best of our knowledge. When the bias is neutral, the model is reduced to a mean-field voter model. We analyze the behavior and steady states of the system, identifying three distinct regimes based on the bias level: one favoring negative opinions, one favoring positive opinions, and a neutral case. In large systems, the equilibrium properties become independent of the size of the group, indicating that only the bias influences the final outcome. However, for small groups, the time to reach equilibrium depends on the size of the group. Our results show that even a small initial bias leads to a consensus where all agents eventually share the same opinion when the bias is not neutral. The system exhibits universal behavior, with critical slowing down occurring near the neutral bias point, marking it as a critical dynamical threshold. The time required to reach consensus scales logarithmically when the bias is non-neutral and linearly when it is neutral. Although short-term dynamics depends on group size for small groups, long-term behavior is governed solely by the bias.