Opinion and community formation in coevolving networks

TL;DR

This paper presents a dynamic agent-based model for coevolving social networks and opinions, highlighting how different interaction scales influence community formation and opinion consensus.

Contribution

It introduces a novel coevolutionary model incorporating short and long-range interactions, external influences, and opinion-dependent network rewiring.

Findings

Well-connected opinion-based communities emerge due to scale separation.

Numerical simulations and mean field analysis confirm community formation dynamics.

The model highlights the impact of external fields and biases on opinion spread.

Abstract

In human societies opinion formation is mediated by social interactions, consequently taking place on a network of relationships and at the same time influencing the structure of the network and its evolution. To investigate this coevolution of opinions and social interaction structure we develop a dynamic agent-based network model, by taking into account short range interactions like discussions between individuals, long range interactions like a sense for overall mood modulated by the attitudes of individuals, and external field corresponding to outside influence. Moreover, individual biases can be naturally taken into account. In addition the model includes the opinion dependent link-rewiring scheme to describe network topology coevolution with a slower time scale than that of the opinion formation. With this model comprehensive numerical simulations and mean field calculations have been carried out and they show the importance of the separation between fast and slow time scales resulting in the network to organize as well-connected small communities of agents with the same opinion.