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A Game Theoretic Model of Adversaries and Media Manipulation

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  • Kjell Hausken

    (Faculty of Science and Technology, University of Stavanger, 4036 Stavanger, Norway)

Abstract

A model is developed for two players exerting media manipulation efforts to support each of two actors who interact controversially. Early evidence may support one actor, while the full evidence emerging later may support the other actor. Exerting effort when the full evidence exceeds (falls short off) the early evidence is rewarded (punished) with lower (higher) unit effort cost. Properties and simulations are presented to illustrate the players’ strategic challenges when altering eight model parameters, i.e., a player’s unit effort cost, stake in the interaction, proportionality parameter scaling the strength of reward or punishment, time discount parameter, early evidence, full evidence, contest intensity, and evidence ratio intensity. Realizing the logic of the model may aid understanding on how to handle the difference between early and full evidence of controversies, in which players have an ideological stake.

Suggested Citation

  • Kjell Hausken, 2019. "A Game Theoretic Model of Adversaries and Media Manipulation," Games, MDPI, vol. 10(4), pages 1-15, December.
    • Handle: RePEc:gam:jgames:v:10:y:2019:i:4:p:48-:d:293180
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    References listed on IDEAS

    as
    1. Hausken, Kjell, 2008. "Whether to attack a terrorist's resource stock today or tomorrow," Games and Economic Behavior, Elsevier, vol. 64(2), pages 548-564, November.
    2. Hirshleifer, Jack & Osborne, Evan, 2001. "Truth, Effort, and the Legal Battle," Public Choice, Springer, vol. 108(1-2), pages 169-195, July.
    3. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    4. Kjell Hausken & Gregory Levitin, 2008. "Efficiency of Even Separation of Parallel Elements with Variable Contest Intensity," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1477-1486, October.
    5. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
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    Cited by:

    1. Kjell Hausken, 2020. "Game theoretic analysis of ideologically biased clickbait or fake news and real news," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(2), pages 39-57.

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