Modelling a network where the opinion of each unit varies according to a majority ruling of its neighbouring units

TL;DR

This paper models a community network where individuals adopt opinions based on majority rule, revealing how initial conditions lead to segregation or dominance, with implications for social, neural, and ecological systems.

Contribution

It introduces a lattice-based model of opinion dynamics driven by majority rule, analyzing the conditions leading to community segregation or consensus.

Findings

Community segregates into gangs or becomes opinion-dominated based on initial ratios.

Gangs are separated by neutral or confused groups, buffering opinion transitions.

Model applies to social, neural, and ecological networks.

Abstract

The complexity of human behaviour can lead to very unpredictable patterns in social activity and structure. Here we demonstrate the instability of a community network controlled by majority ruling, where an element adopts the most popular opinion of their peers. We modelled a community as a square lattice, and performed sequential time step numerical calculations upon each cell in parallel. Depending on the initial ratio of two opinions, the community can segregate either into separate gangs and cliques, or get dominated by a single opinion. We also note that gangs are separated by neutral or confused groups of individuals, buffering the transition. The behaviors shown by this model can be comfortably applied to many other real life situations, such as neural or ecological networks. The results of this paper have been preliminary published in the Ref. [34].