Social influence estimation in Friedkin and Johnsen’s opinion dynamics over sparse networks

Date and Location

Mar 16, 2018 - 3:00pm to 4:00pm
Webb 1100


Chiara Ravazzi
National Research Council of Italy (CNR)
Institute of Electronics, Computer and Telecommunication Engineering (IEIIT)


In this talk we study a novel methodology for estimating the social influence among agents interacting in a sparse social network described by the Friedkin and Johnsen’s model. In this classical model, n agents discuss m << n topics, are influenced by the others’ opinions, but are not completely open-minded, being persistently driven by their initial opinions. We reconstruct the social network topology and the strength of the interconnections starting from observations of the initial and final opinions’ profile only. The intrinsic sparsity of the graph is exploited via an l_0/l_1 minimization. The techniques previously proposed in the literature assume partial knowledge of the social graph or place in an optimized way external stubborn agents injecting prescribed inputs, thus changing the terminal behavior of the opinion dynamics. We are able to drop both these assumptions. Under suitable conditions, we derive theoretical guarantees that the problem is well posed and sufficient requirements on the number of topics under discussion that ensure perfect recovery. Extensive simulations on synthetic and real networks corroborate theoretical results.

Chiara Ravazzi received the B.Sc., M.Sc., and Ph.D. degrees from the Politecnico di Torino,Italy, in 2005, 2007, and 2011, respectively, all in applied mathematics. In 2010, she was a Visiting Member with the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge. From 2011 to 2012, she was a Research Assistant with the Department of Mathematics, Politecnico di Torino. From 2012 to 2016, she held a post-doctoral position with the Department of Electronics and Telecommunications, Politecnico di Torino, where she was involved in developing algorithms for sparse recovery problems, within the project Towards Compressive Information Processing Systems funded by the European Union as ERC starting grant (2012-2016). From 2013 to 2016, she was a Research Associate with the National Research Council of Italy (CNR), Institute of Electronics, Computer and Telecommunication Engineering (IEIIT). Since 2017, she has been a Tenured Researcher with the CNR-IEIIT, working in the Systems Modeling & Control Group. Her current research interests include signal processing, optimization and control of network systems.

Sponsored by the Center for Control, Dynamical Systems, and Computation