Opinion Dynamics on Networks under Correlated Disordered External Perturbations

• Published in: Journal of statistical physics Vol. 173; no. 1; pp. 54 - 76
• Main Authors: Ramos, Marlon, de Aguiar, Marcus A. M., Braha, Dan
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2018; Springer; Springer Nature B.V
• Subjects: Analysis; AUGMENTATION; CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; Complex systems; Correlation analysis; CORRELATIONS; DISTRIBUTION; DISTURBANCES; Dynamic response; EQUATIONS; Financial markets; FLUCTUATIONS; Mathematical and Computational Physics; Mathematical models; MEAN-FIELD THEORY; Network topologies; PERTURBATION THEORY; PHASE TRANSFORMATIONS; Phase transitions; Physical Chemistry; Physics; Physics and Astronomy; Population genetics; Quantum Physics; Social networks; SPIN; Statistical Physics and Dynamical Systems; Target marketing; Theoretical; Transportation networks; Variation; Voters; Critical phenomena; Opinion dynamics; Disorder; Complex networks
• ISSN: 0022-4715; 1572-9613
• DOI: 10.1007/s10955-018-2135-5

We study an influence network of voters subjected to correlated disordered external perturbations, and solve the dynamical equations exactly for fully connected networks. The model has a critical phase transition between disordered unimodal and ordered bimodal distribution states, characterized by an increase in the vote-share variability of the equilibrium distributions. The fluctuations (variance and correlations) in the external perturbations are shown to reduce the impact of the external influence by increasing the critical threshold needed for the bimodal distribution of opinions to appear. The external fluctuations also have the surprising effect of driving voters towards biased opinions. Furthermore, the first and second moments of the external perturbations are shown to affect the first and second moments of the vote-share distribution. This is shown analytically in the mean field limit, and confirmed numerically for fully connected networks and other network topologies. Studying the dynamic response of complex systems to disordered external perturbations could help us understand the dynamics of a wide variety of networked systems, from social networks and financial markets to amorphous magnetic spins and population genetics.