Noise-based control of opinion dynamics

TL;DR

This paper presents a rigorous theoretical analysis and simulations demonstrating that noise-based control strategies, affecting only a fraction of individuals, can efficiently induce consensus in opinion dynamics.

Contribution

It introduces a novel noise-based control method for opinion formation that requires minimal intervention and provides theoretical insights into its effectiveness.

Findings

System can reach quasi-consensus with any number of noise-affected individuals.

Critical noise strength for consensus can be explicitly determined.

Noise-driven control is effective even with only one individual affected.

Abstract

Designing feasible control strategies for opinion dynamics in complex social systems has never been an easy task. It requires a control protocol which 1) is not enforced on all individuals in the society, and 2) does not exclusively rely on specific opinion values shared by the social system. Thanks to the recent studies on noise-induced consensus in opinion dynamics, the noise-based intervention strategy has emerged as the only one meeting both of the above requirements, yet its underlying general theory is still lacking. In this paper, we perform rigorous theoretical analysis and simulations of a noise-based control strategy for opinion formation in which only a fraction of individuals is affected by randomly generated noise. We found that irrespective of the number of noise-driven individuals, including the case of only one single noise-affected individual, the system can attain a quasi-consensus in finite time, and the critical noise strength can be obtained. Our results highlight the efficiency of noise-driven mechanisms for the control of complex social dynamics.