Mohammad Amin Fazli

Assistant Professor

Maximizing the Spread of Social Norms in Social Networks

  Halls department, Hall 3
  Thursday, 28 December 2017
  12:00 - 13:00


Social norms are a core concept in social sciences and play a critical role in regulating a society’s behaviors. Organizations and even governmental bodies use this social component to tackle varying challenges in society, as it is a less costly alternative to establishing new laws and regulations. Social networks are an important and effective infrastructure in which social norms can evolve. Therefore there is a need for theoretical models for studying the spread of social norms in social networks.

In this talk, by using the intrinsic properties of norms, we redefine and tune the Rescorla-Wagner conditioning model in order to obtain an effective model for the spread of social norms. We extend this model for a network of people as a Markov chain. The potential structures of steady states of this process are studied. Then, we formulate the problem of maximizing the adoption of social norms in a social network by finding the best set of initial norm adopters. Finally, we propose a polynomial time algorithm.


Mohammad Amin Fazli received his BSc in hardware engineering and MSc and PhD in software engineering from Sharif University of Technology, in 2009, 2011 and 2015 respectively. He is currently an assistant professor at Sharif University of Technology and R\&D Supervisor at Sharif's Intelligent Information Solutions Center resided in this university. His research interests include Game Theory, Combinatorial Optimization, Computational Business and Economics, Graphs and Combinatorics, Complex networks and Dynamical Systems.