Minimizing the misinformation spread in social networks. (2nd August 2020)

• Record Type: Journal Article
• Authors: Tanınmış, Kübra; Aras, Necati; Altınel, İ. Kuban; Güney, Evren
• Is Part Of: IISE transactions. Volume 52:Number 8(2020)
• Page Start: 850
• Page End: 863
• Publication Date: 2020-08-02
• Subjects: Influence minimization -- bilevel modeling -- Stackelberg game -- stochastic optimization; Industrial engineering -- Periodicals; Systems engineering -- Periodicals; Industrial engineering; Systems engineering; Electronic journals; Periodicals; 670.285
• DOI: 10.1080/24725854.2019.1680909
• Languages: English
• ISSNs: 2472-5854

Abstract

Abstract: The Influence Maximization Problem has been widely studied in recent years, due to rich application areas including marketing. It involves finding k nodes to trigger a spread such that the expected number of influenced nodes is maximized. The problem we address in this study is an extension of the reverse influence maximization problem, i.e., misinformation minimization problem where two players make decisions sequentially in the form of a Stackelberg game. The first player aims to minimize the spread of misinformation whereas the second player aims its maximization. Two algorithms, one greedy heuristic and one matheuristic, are proposed for the first player's problem. In both of them, the second player's problem is approximated by Sample Average Approximation, a well-known method for solving two-stage stochastic programming problems, that is augmented with a state-of-the-art algorithm developed for the influence maximization problem.