Nonlinear $q$-voter model involving nonconformity on networks

TL;DR

This paper investigates how nonconformist behaviors like anticonformity and independence influence opinion phase transitions on networks, revealing continuous and discontinuous transitions and universality class similarities to the mean-field Ising model.

Contribution

It introduces a nonlinear $q$-voter model with a skepticism parameter on networks, analyzing the effects of nonconformity on phase transitions and universality classes.

Findings

Model exhibits both continuous and discontinuous phase transitions.

Complete graph and scale-free network share universality with mean-field Ising model.

Scaling behavior depends on skepticism parameter and nonconformity probability.

Abstract

The order-disorder phase transition is a fascinating phenomenon in opinion dynamics models within sociophysics. This transition emerges due to noise parameters, interpreted as social behaviors such as anticonformity and independence (nonconformity) in a social context. In this study, we examine the impact of nonconformist behaviors on the macroscopic states of the system. Both anticonformity and independence are parameterized by a probability \( p \), with the model implemented on a complete graph and a scale-free network. Furthermore, we introduce a skepticism parameter \( s \), which quantifies a voter's propensity for nonconformity. Our analytical and simulation results reveal that the model exhibits continuous and discontinuous phase transitions for nonzero values of \( s \) at specific values of \( q \). We estimate the critical exponents using finite-size scaling analysis to classify the model's universality. The findings suggest that the model on the complete graph and the scale-free network share the same universality class as the mean-field Ising model. Additionally, we explore the scaling behavior associated with variations in \( s \) and assess the influence of \( p \) and \( s \) on the system's opinion dynamics.