Conformism-driven phases of opinion formation on heterogeneous networks: the q-voter model case

TL;DR

This paper investigates how conformist and non-conformist behaviors influence opinion formation on heterogeneous networks using the q-voter model, revealing phase transitions driven by conformist density across different network topologies.

Contribution

It introduces a simulation of the q-voter model with mixed conformist behaviors on realistic network topologies, highlighting the impact of conformist density on opinion phases.

Findings

Conformist density thresholds induce phase transitions in opinion states.

Different network topologies exhibit distinct critical conformist densities.

Consensus is more easily achieved with higher conformist proportions.

Abstract

The q-voter model, a variant of the classic voter model, has been analyzed by several authors: while allowing to study opinion dynamics, this model is also believed to be one of the most representative among the many defined in the wide field of sociophysics. Here, we investigate the consequences of conformity on the consensus reaching process, by numerically simulating a q-voter model with agents behaving either as conformists or non-conformists, embedded on heterogeneous network topologies (as small-world and scale-free). In fact, although it is already known that conformity enhances the reaching of consensus, the related process is often studied only on fully-connected networks, thus strongly limiting our full understanding of it. This paper represents a first step in the direction of analyzing more realistic social models, showing that different opinion formation-phases, driven by the conformist agents density, are observable. As a result, we identify threshold values of the density of conformist agents, varying across different topologies and separating different regimes of our system, ranging from a disordered phase, where different opinions coexist, to a gradually more ordered phase, where consensus is eventually reached.