Research Scientist at Center for Scientific Innovation and Education (CSIE), UIUC
Friday, May 19, 2023
Conference room, Institute of Mathematics
Opinion dynamics models analyze social networks by measuring each individual's attitude toward a particular action, topic, or goal. By studying opinion dynamics, we can gain valuable insights into how opinions and beliefs spread through social networks and how individuals are influenced by their peers.
Relying on the theory of MFG and incorporating the insights of the bounded confidence model (Hegselmann-Krause model), we have developed multi-population opinion dynamics models. The proposed models are scalable in terms of controllable agents and sensitive regarding sub-population affiliations. The models effectively capture various social phenomena, including consensus, polarization, and fragmentation, allowing us to better understand opinion evolution in social networks.