Opinion Dynamics and Influence in Social Networks

Almost all important social decisions are taken by individuals on the basis of their opinions, which are formed and updated as a result of their experiences, observations of others’ actions, and news, propaganda and indoctrination from media sources, political leaders and the state. In this talk, we present our recent work on opinion dynamics and influence in social networks. We study a stochastic gossip model of opinion dynamics in a society consisting of two types of agents: regular agents, who update their beliefs according to information that they receive from their social neighbors; and prominent agents with disproportionate impact on the opinions of the rest of the society.

We first consider the case when prominent agents obtain some information from others. We show that in this case all beliefs converge to a stochastic consensus. Our main results quantify the extent of their influence by providing bounds or exact results on the gap between the consensus value and the benchmark without prominent agents (where there is efficient information aggregation). We then consider the case when prominent agents are fully stubborn, i.e., they never update their opinions. In this case, opinion dynamics never lead to a consensus (among the regular agents). Instead, beliefs in the society almost surely fail to converge, and the belief of each regular agent converges in law to a non-degenerate random variable. The model in this case thus generates long-run disagreement and continuous opinion fluctuations. We provide explicit characterizations of the expected values and correlations of the limiting beliefs. We also present bounds on the dispersion of the expected values and variances of limiting beliefs as a function of the structure of the underlying social network and the location of the stubborn agents.

Speaker Details

Asu Ozdaglar received the B.S. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey, in 1996, and the S.M. and the Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1998 and 2003, respectively.

Since 2003, she has been a member of the faculty of the Electrical Engineering and Computer Science Department at the Massachusetts Institute of Technology, where she is currently the Class of 1943 Associate Professor. She is also a member of the Laboratory for Information and Decision Systems and the Operations Research Center. Her research interests include optimization theory, with emphasis on nonlinear programming and convex analysis, game theory, with applications in communication, social, and economic networks, and distributed optimization and control. She is the co-author of the book entitled “Convex Analysis and Optimization” (Athena Scientific, 2003).

Professor Ozdaglar is the recipient of a Microsoft fellowship, the MIT Graduate Student Council Teaching award, the NSF Career award, the 2008 Donald P. Eckman award of the American Automatic Control Council, and is a 2011 Kavli Fellow of the National Academy of Sciences. She served on the Board of Governors of the Control Systems Society in 2010 and is currently the chair of the working group “Game-Theoretic Methods in Networks” under the Technical Committee “Networks and Communication Systems”.

Date:
Speakers:
Asu Ozdaglar
Affiliation:
MIT