Analysis of information diffusion with irrational users: A graphical evolutionary game approach

Abstract

Modeling and analysis of information diffusion over networks is of crucial importance to better understand the avalanche of information flow over social networks and to investigate its impact on economy and our social life. Different from prior works that study rational behavior in information diffusion, we focus on “irrational users”, e.g., those who always inten-tionally forward fake news even when they know it contains false information. We extend the graphical evolutionary game model for information diffusion, and analyze the impact of such irrational behavior on information propagation. Our simulation results on synthetic networks are consistent with our analytical results, and they show that even a few irrational users can significantly increase the number of users who adopt the forwarding strategy.

Benliu Qiu

PhD student

My research interests include continual learning, transfer learning, object detection, multimodality, social network analysis and game theory.