A relative approach to opinion formation

TL;DR

This paper introduces a relative opinion formation model that focuses on opinions' positions relative to each other, enabling analysis of complex dynamics like polarization and consensus using matrix theory.

Contribution

It proposes a novel relative opinion modeling approach, extending influence weight analysis to derive long-term opinion behaviors under relaxed conditions.

Findings

Identifies stable opinion patterns hidden in relative frameworks

Provides a closed-form long-term dynamic description for two-agent systems

Derives conditions for subgroup influence to affect overall population

Abstract

Formal models of opinion formation commonly represent an individual's opinion by a value on a fixed opinion interval. We propose an alternative modeling method wherein interpretation is only provided to the relative positions of opinions vis-\`a-vis each other. This method is then considered in a similar setting as the discrete-time Altafini model (an extension of the well-known DeGroot model), but with more general influence weights. Even in a linear framework, the model can describe, in the long run, polarization, dynamics with a periodic pattern, and (modulus) consensus formation. In addition, in our alternative approach key characteristics of the opinion dynamic can be derived from real-valued square matrices of influence weights, which immediately allows one to transfer matrix theory insights to the field of opinion formation dynamics under more relaxed conditions than in the DeGroot or discrete-time Altafini models. A few specific themes are covered: (i) We demonstrate how stable patterns in relative opinion dynamics are identified which are hidden when opinions are considered in an absolute opinion framework. (ii) For the two-agent case, we provide an exhaustive closed-form description of the relative opinion model's dynamic in the long run. (iii) We explore group dynamics analytically, in particular providing a non-trivial condition under which a subgroup's asymptotic behavior carries over to the entire population.