Diffusion-driven pattern formation in an opinion dynamical network model

TL;DR

This paper investigates how community structure and agent migration influence opinion diversity, revealing conditions under which spatial patterns sustain minority opinions through a network-based model.

Contribution

It introduces an analytical framework for understanding diffusion-driven pattern formation in opinion networks, linking community structure to opinion diversity.

Findings

Structural features of networks can sustain opinion diversity.

Diffusion-driven patterns enable minority opinions to persist.

Analytical conditions for pattern formation are derived.

Abstract

The spatial organization of individuals and their interactions in communities are important factors known to preserve diversity in many complex systems. Inspired by metapopulation models from ecology, we study opinion formation using a network-based approach in which nodes represent communities of interacting agents holding one of two competing opinions, and links represent avenues of migration. Agents adapt to the dominant opinion within a community or migrate toward communities with similar views. Using a master stability function approach, we analytically derive conditions for diffusion-driven pattern formation and identify structural features of the community network that sustain opinion diversity. Our model shows that even under minimal opinion rules, the interaction between local dynamics and community structure generates spatial patterns that allow minority opinions to persist by gaining local dominance.