Opinion Dynamics on Networks

When people interact with each other, their opinions evolve. For several decades, researchers from mathematics, the social sciences, and many other areas have developed and studied many models of opinion dynamics. In this talk, I will discuss the modeling of opinion dynamics on various types of networks. I will start by introducing some general questions and ideas in the modeling of social dynamics. I will then focus on bounded-confidence models (BCMs), in which individual entities have continuous-valued opinions and update their opinions when they interact with entities with sufficiently similar opinions. I will discuss various generalizations of BCMs and examine how they affect consensus, polarization, and fragmentation of opinions in BCMs.

Bio
https://www.math.ucla.edu/~mason/