With the emergence of online social networks as a primary platform for advertising and advocacy, enhancing a user’s influence has become of significant interest. In this talk, we will address this problem under the Friedkin-Johnsen opinion dynamics model, wherein stubborn agents influence the opinions of other agents in the network. We propose to use edge modifications, specifically those which mimic the mechanism of recommendations in social networks. In such scenarios, topological properties of the network play a key role in increasing the influence of a desired stubborn agent. Hence, we will show that there exist topology-based conditions that identify the edge modifications that always increase the influence of a desired stubborn agent. Interestingly, the impact of the chosen edge modifications is robust to changes in parameters such as stubbornness and the interaction weights. Finally, we will demonstrate the effectiveness of our approach over the Erdos–Renyi random graph.
Twinkle Tripathy is currently an Assistant Professor in the Department of Electrical Engineering of IIT Kanpur. She received a Dual Degree of M.Tech. and Ph.D. at Systems & Control Engineering, IIT Bombay in Dec. 2016. Thereafter, she served at the School of Electrical & Electronic Engineering, NTU, Singapore and with the Faculty of Aerospace Engineering, Technion - Israel Institute of Technology as a post-doctoral fellow till Aug. 2020. Her research interests broadly include control and guidance of autonomous systems and opinion dynamics. She is a senior member of IEEE and is the recipient of the Best Woman Professional Award in the early career category awarded by the IEEE India Council under the Pralhad P. Chhabria Awards.