Title: The significance and learning of interaction structure in social networks
Abstract: This talk focuses on the significance and learning of peer-to-peer interaction graphs in social networks. Peer opinions and decisions are inherently interconnected. The structure of interpersonal interactions is known to play a critical role in understanding trends of dynamic opinions or equilibriums in multi-agent decision making. First of all, we investigate the significance of the interaction graph in the decade-long international negotiations under the United Nations Framework Convention on Climate Change (UNFCCC) that led to the 2015 Paris Agreement on climate change. The UNFCCC negotiations were held in forms of sequential plenary meetings between all parties and group meetings between auxiliary bodies. Taking the meeting participations as the (time-varying) interaction graph among the UNFCCC nations, we show a concatenated Friedkin-Johnsen (FJ) model manages to describe the multi-year negations as an opinion dynamic process, and as a result, the social power of UNFCCC nations in terms of their percentage-wise influence on the 2015 Paris Agreement is obtained. Next, we turn to the possibility of learning thesocial interaction graph from online data, where users’ decisions are viewed as rational decisions from certain underlying linear quadratic network games. It is shown that learning the interaction graph is a behavioral system identification problem, where system behaviors such as sparsity, homophily, and social stability enhance the learning efficiency. This game-theoretic learning of social interaction graph is demonstrated to be more robust compared to existing benchmark approaches on a real-world YELP dataset.
Bio: Guodong Shi received the B.Sc. degree in mathematics and applied mathematics from the School of Mathematics, Shandong University, Jinan, China in 2005, and the Ph.D. degree in systems theory from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China in 2010. From 2010 to 2014, he was a Postdoctoral Researcher at the ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden. From 2014 to 2018, he was with the Research School of Engineering, The Australian National University, Canberra, ACT, Australia, as a Lecturer and then Senior Lecturer, and a Future Engineering Research Leadership Fellow. Since 2019 he has been with the Australian Center for Field Robotics, The University of Sydney, NSW 2006, Sydney, Australia as a Senior Lecturer. His research interests include distributed control systems, quantum networking and decisions, and social opinion dynamics.
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