OPINION DYNAMICS AND INFORMATION CASCADES
Game theory is a natural choice for a mathematical language with which we can talk about the evolution of reasoned behaviors in a social context. Specifically, game theory is the study of the ways in which interacting choices of economic agents produce outcomes with respect to the preferences (or utilities) of those agents, where the outcomes in question might have been intended by none of the agents. In recent work, we use game theory to formally characterize peer influence in the context of opinion dynamics and information cascades. In so doing, we hope to gain insight into the mechanisms behind observed phenomena and provide model-based approaches for forecasting and prediction.
C. Griffin, S. Rajtmajer, A. Squicciarini, A. Belmonte. Consensus and Information Cascades in Game-Theoretic Imitation Dynamics with Static and Dynamic Network Topologies. SIAM Journal on Applied Dynamical Systems (SIADS), April 2019.
J. Semonsen, C. Griffin, A. Squicciarini, S. Rajtmajer. Opinion Dynamics in the Presence of Increasing Agreement Pressure. IEEE Transactions on Cybernetics. February 2018.
J. Semonsen, C. Griffin, A. Squicciarini, and S. Rajtmajer. Consensus on Social Graphs under Increasing Peer Pressure (Extended Abstract). International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.