Threshold Models for Competitive Influence in Social Networks

  • Allan Borodin
  • Yuval Filmus
  • Joel Oren
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6484)

Abstract

The problem of influence maximization deals with choosing the optimal set of nodes in a social network so as to maximize the resulting spread of a technology (opinion, product-ownership, etc.), given a model of diffusion of influence in a network. A natural extension is a competitive setting, in which the goal is to maximize the spread of our technology in the presence of one or more competitors.

We suggest several natural extensions to the well-studied linear threshold model, showing that the original greedy approach cannot be used.

Furthermore, we show that for a broad family of competitive influence models, it is NP-hard to achieve an approximation that is better than a square root of the optimal solution; the same proof can also be applied to give a negative result for a conjecture in [2] about a general cascade model for competitive diffusion.

Finally, we suggest a natural model that is amenable to the greedy approach.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Allan Borodin
    • 1
  • Yuval Filmus
    • 1
  • Joel Oren
    • 1
  1. 1.Department of Computer ScienceUniversity of TorontoCanada

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