A Refined Theory of Opinion Dynamics and Its Applications

In this 51-minute BIMSA Member Seminar, Professor Xiaoming Zhang presents a refined theory of opinion dynamics and its applications to political polarization. Explore the development history of micro-scale governing equations for opinion dynamics before delving into a refined model based on empirical data. Discover how this model analyzes opinion distributions in the US Congress using 154 years of recorded data, addressing key questions about what drives ideological separation and reunion in the U.S. political system, and whether relationships exist between partisan polarization and critical historical events. Dr. Zhang, who holds degrees from Zhejiang University, Peking University, and MIT, currently serves as a professor at the Beijing Institute of Mathematical Sciences and Applications, focusing on developing machine learning algorithms driven by both data and domain knowledge to interpret various physical, biological, and social phenomena.