Strategic Seeding of Rival Opinions

  • Samuel D. Johnson
  • Jemin George
  • Raissa M. D’Souza
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 174)


We present a network influence game that models players strategically seeding the opinions of nodes embedded in a social network. A social learning dynamic, whereby nodes repeatedly update their opinions to resemble those of their neighbors, spreads the seeded opinions through the network. After a fixed period of time, the dynamic halts and each player’s utility is determined by the relative strength of the opinions held by each node in the network vis-à-vis the other players. We show that the existence of a pure Nash equilibrium cannot be guaranteed in general. However, if the dynamics are allowed to progress for a sufficient amount of time so that a consensus among all of the nodes is obtained, then the existence of a pure Nash equilibrium can be guaranteed. The computational complexity of finding a pure strategy best response is shown to be \(\mathrm {NP}\)-complete, but can be efficiently approximated to within a \((1 - 1/e)\) factor of optimal by a simple greedy algorithm.


Social networks Opinion dynamics Game theory Nash equilibrium Computational complexity Approximation algorithm 



The authors gratefully acknowledge support from the US Army Research Office MURI Award No. W911NF-13-1-0340 and Cooperative Agreement No. W911NF-09-2-0053.


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Authors and Affiliations

  • Samuel D. Johnson
    • 1
  • Jemin George
    • 2
  • Raissa M. D’Souza
    • 3
  1. 1.HRL Laboratories, LLCMalibuUSA
  2. 2.United States Army Research LaboratoryAdelphiUSA
  3. 3.University of CaliforniaDavisUSA

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