Endüstri Mühendisliği Seminerler Serisi - Necati Aras

Title: Influence Maximization with Deactivation In Social Networks

Abstract: In this paper we consider an extension of the well-known Influence Maximization Problem (IMP) in a social network which deals with finding an initial set of k nodes to initiate a diffusion process in the network so that the total number of affected nodes at the end of the process is maximized. The extension focuses on a competitive variant of IMP where two decision makers are involved. The first one, the leader, tries to maximize the total influence spread by selecting the most influential nodes and the second one, the follower, tries to minimize it by deactivating some of these nodes. The formulated bilevel model is solved by complete enumeration for small-sized instances and by a matheuristic for large-sized instances. In both cases, the lower level problem, which is a stochastic optimization problem, is approximated via the Sample Average Approximation method.

Bio: Necati Aras is Associate Professor of Industrial Engineering at Boğaziçi University. He holds a Ph.D. in Industrial Engineering from Boğaziçi University. He was a postdoctoral research fellow at the Desautels Faculty of Management of McGill University during 2000-2002. Before joining the department in 2003, he worked for 6 years in private sector, the last two years of which was with a training and consulting company. His current research interests include facility location problems, reverse logistics, closed-loop supply chains, wireless sensor networks, and social networks. He has published more than 50 papers in scholarly journals. (A detailed list of all publications can be found on his personal web site (http://www.ie.boun.edu.tr/~aras).