Coevolutionary Dynamics of Actions and Opinions in Social Networks

• 成果类型: Article
• 署名作者: Aghbolagh, Hassan Dehghani; Ye, Mengbin; Zino, Lorenzo; Chen, Zhiyong; Cao, Ming
• 署名单位: University of Newcastle; Curtin University; University of Groningen; Polytechnic University of Turin; University of Groningen
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3290771
• 发表日期: 2023
• 页码: 7708-7723
• 关键词: decision making; dynamics on networks; evolutionary game theory; opinion dynamics; polarization

摘要

Empirical studies suggest a deep intertwining between opinion formation and decision-making processes, but these have been treated as separate problems in the study of dynamical models for social networks. In this article, we bridge the gap in the literature by proposing a novel coevolutionary model, in which each individual selects an action from a binary set and has an opinion on which action they prefer. Actions and opinions coevolve on a two-layer network. For homogeneous parameters, undirected networks, and under reasonable assumptions on the asynchronous updating mechanics, we prove that the coevolutionary dynamics is an ordinal potential game, enabling analysis via potential game theory. Specifically, we establish global convergence to the Nash equilibria of the game, proving that actions converge in a finite number of time steps, while opinions converge asymptotically. Next, we provide sufficient conditions for the existence of, and convergence to, polarized equilibria, whereby the population splits into two communities, each selecting and supporting one of the actions. Finally, we use simulations to examine the social psychological phenomenon of pluralistic ignorance.