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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)

Abstract

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.

Keywords

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

Notes

Acknowledgements

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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