Location-Based Competitive Influence Maximization in Social Networks

  • Manh M. Vu
  • Huan X. HoangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11917)


Although the competitive influence maximization (CIM) problem has been extensively studies, existing works ignore the fact that location information can play an important role in influence propagation. In this paper, we study the location-based competitive influence maximization (LCIM) problem, which aims to select an optimal set of users of a player or a company to maximize the influence for given query region, while at the same time their competitors are conducting a similar strategy. We propose a greedy algorithm with \((1-1/e-\epsilon )\) approximation ratio and a heuristic algorithm LCIM-MIA based on MIA structure. Experimental results on real-world datasets show that our methods often better than several baseline algorithms.


Location-based Competitive influence maximization Diffusion model Social networks 



This work is supported by VNU University of Engineering and Technology under project number CN 18.07.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of Engineering and Technology, Vietnam National UniversityHanoiViet Nam
  2. 2.Faculty of Information and SecurityPeople’s Security AcademyHanoiViet Nam

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