Modelling opinion formation driven communities in social networks

TL;DR

This paper models opinion formation in social networks through a co-evolution process involving fast interactions and slow network changes, highlighting how individual biases influence community structures.

Contribution

It introduces a dual-time-scale model incorporating personal biases and network rewiring, revealing their effects on opinion dynamics and community formation.

Findings

Communities emerge depending on the ratio of time scales.

Individual biases significantly influence opinion conformation.

The model captures social behavior patterns through numerical simulations.

Abstract

In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter $\alpha$, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realized by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter $\alpha$ and its influence on the conformation of opinion and the size of the resulting communities. We present numerical studies and extract interesting features of the model that can be interpreted in terms of social behaviour.