Coevolutionary Dynamics of Actions and Opinions in Social Networks

Speaker: 曹明教授，荷兰格罗宁根大学人工智能学院院长

Inviter: 系统所

Title: Coevolutionary Dynamics of Actions and Opinions in Social Networks

Language: English

Time & Venue: 2024.11.14  15:00-16:30   N202

Abstract: The comparison between media predictions and final outcome of the most recent US presential election shows the complexity of understanding social interactions in large populations. Empirical studies of human social networks 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 talk, I will show how to bridge this gap by utilizing a novel coevolutionary model, in which everyone 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 form 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, which sheds light on perplexing social decision-making processes.