Noise-Based Control of Opinion Dynamics (Wei Su, Xianzhong Chen, Yongguang Yu, Ge Chen)


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.



IEEE Transactions on Automatic Control, Volume 67, Issue 6, June 2022



Wei Su

School of Science, Beijing Jiaotong University, Beijing, China


Xianzhong Chen

Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China


Yongguang Yu

School of Science, Beijing Jiaotong University, Beijing, China


Ge Chen

National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China