Title: Clustering in Opinion Dynamics and Evolution of Self-Apraisals
Abstract: The talk will focus on two discrete-time models for opinion dynamics in social networks. The first part will consider a discrete-time modulus consensus model in which the interaction among a group of individuals is described by a time-dependent, complex-valued, weighted digraph. It is shown that for any sequence of repeatedly jointly strongly connected digraphs, without any assumption on the structure of the complex-valued weights, the system asymptotically reaches modulus consensus. The second part will address a study of the opinion dynamics that emerge in a scenario where individuals consecutively discuss a sequence of issues. Specifically, we will discuss how individuals’ self-confidence levels evolve via a reflected appraisal mechanism. Motivated by the DeGroot-Friedkin model, we will introduce a Modified DeGroot-Friedkin (MDGF) model, which allows individuals to update their self-confidence levels by interacting with only their neighbors. In particular, the modified model allows the update of self-confidence levels to take place in finite time without waiting for the opinion process to reach consensus on any particular issue.
Bio: Ji Liu received the Ph.D. degree in electrical engineering from Yale University in 2013. He is currently an Assistant Professor in the Department of Electrical and Computer Engineering at Stony Brook University. He was a Postdoctoral Research Associate at University of Illinois at Urbana-Champaign and Arizona State University. His current research interests include distributed control and computation, multi-agent systems, social networks, epidemic networks, and power networks. URL: https://sites.google.com/site/jiliucontrol