Hierarchical Consensus Formation Reduces the Influence of Opinion Bias

TL;DR

This paper investigates how hierarchical decision-making structures can mitigate opinion bias in collective consensus formation, demonstrating that such hierarchies lead to more accurate aggregation of individual opinions.

Contribution

It introduces a two-step hierarchical model for opinion dynamics that reduces bias impact and improves consensus accuracy compared to non-hierarchical models.

Findings

Hierarchical structures bring the collective opinion closer to the true average.

Group size of representatives influences the effectiveness of bias reduction.

Hierarchies can optimize decision-making in organizational settings.

Abstract

We study the role of hierarchical structures in a simple model of collective consensus formation based on the bounded confidence model with continuous individual opinions. For the particular variation of this model considered in this paper, we assume that a bias towards an extreme opinion is introduced whenever two individuals interact and form a common decision. As a simple proxy for hierarchical social structures, we introduce a two-step decision making process in which in the second step groups of like-minded individuals are replaced by representatives once they have reached local consensus, and the representatives in turn form a collective decision in a downstream process. We find that the introduction of such a hierarchical decision making structure can improve consensus formation, in the sense that the eventual collective opinion is closer to the true average of individual opinions than without it. In particular, we numerically study how the size of groups of like-minded individuals being represented by delegate individuals affects the impact of the bias on the final population-wide consensus. These results are of interest for the design of organisational policies and the optimisation of hierarchical structures in the context of group decision making.