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Competitive Influence Maximization in Social Networks

  • Shishir Bharathi
  • David Kempe
  • Mahyar Salek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4858)

Abstract

Social networks often serve as a medium for the diffusion of ideas or innovations. An individual’s decision whether to adopt a product or innovation will be highly dependent on the choices made by the individual’s peers or neighbors in the social network. In this work, we study the game of innovation diffusion with multiple competing innovations such as when multiple companies market competing products using viral marketing. Our first contribution is a natural and mathematically tractable model for the diffusion of multiple innovations in a network. We give a (1 − 1/e) approximation algorithm for computing the best response to an opponent’s strategy, and prove that the “price of competition” of this game is at most 2. We also discuss “first mover” strategies which try to maximize the expected diffusion against perfect competition. Finally, we give an FPTAS for the problem of maximizing the influence of a single player when the underlying graph is a tree.

Keywords

Nash Equilibrium Submodular Function Single Player Pure Strategy Nash Equilibrium Perfect Competition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Shishir Bharathi
    • 1
  • David Kempe
    • 1
  • Mahyar Salek
    • 1
  1. 1.Department of Computer Science, University of Southern California 

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