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Influence maximization with deactivation in social networks

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  • Tanınmış, Kübra
  • Aras, Necati
  • Altınel, I.K.

Abstract

In this paper, we consider an extension of the well-known Influence Maximization Problem in a social network which deals with finding a set of k nodes to initiate a diffusion process so that the total number of influenced nodes at the end of the process is maximized. The extension focuses on a competitive variant 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.

Suggested Citation

  • Tanınmış, Kübra & Aras, Necati & Altınel, I.K., 2019. "Influence maximization with deactivation in social networks," European Journal of Operational Research, Elsevier, vol. 278(1), pages 105-119.
    • Handle: RePEc:eee:ejores:v:278:y:2019:i:1:p:105-119
    DOI: 10.1016/j.ejor.2019.04.010
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    References listed on IDEAS

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    8. Fisher, M.L. & Nemhauser, G.L. & Wolsey, L.A., 1978. "An analysis of approximations for maximizing submodular set functions," LIDAM Reprints CORE 341, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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