# Opinion diversity and community formation in adaptive networks

## TL;DR

This paper presents a simple yet powerful model of opinion and network co-evolution that results in a dynamic equilibrium with diversified opinions and interconnected communities, reflecting real-world social dynamics.

## Contribution

It introduces a novel model integrating consensus, rewiring, and opinion change, explaining complex co-evolution dynamics and steady states with multiple communities.

## Key findings

- Formation of interconnected communities without strict consensus
- Existence of phase transitions between different community states
- Insights into opinion distribution and network modularity dynamics

## Abstract

It is interesting and of significant importance to investigate how network structures co-evolve with opinions. The existing models of such co-evolution typically lead to the final states where network nodes either reach a global consensus or break into separated communities, each of which holding its own community consensus. Such results, however, can hardly explain the richness of real-life observations that opinions are always diversified with no global or even community consensus, and people seldom, if not never, totally cut off themselves from dissenters. In this article, we show that, a simple model integrating consensus formation, link rewiring and opinion change allows complex system dynamics to emerge, driving the system into a dynamic equilibrium with co-existence of diversified opinions. Specifically, similar opinion holders may form into communities yet with no strict community consensus; and rather than being separated into disconnected communities, different communities remain to be interconnected by non-trivial proportion of inter-community links. More importantly, we show that the complex dynamics may lead to different numbers of communities at steady state with a given tolerance between different opinion holders. We construct a framework for theoretically analyzing the co-evolution process. Theoretical analysis and extensive simulation results reveal some useful insights into the complex co-evolution process, including the formation of dynamic equilibrium, the phase transition between different steady states with different numbers of communities, and the dynamics between opinion distribution and network modularity, etc.