IDEAS home Printed from https://ideas.repec.org/a/spr/aodasc/v12y2025i3d10.1007_s40745-025-00606-y.html
   My bibliography  Save this article

Rumor Governance Under Uncertain Conditions: An Evolutionary Game Theory Analysis

Author

Listed:
  • Xuefan Dong

    (Beijing University of Technology
    Beijing University of Technology)

  • Lei Tang

    (Beijing University of Technology)

Abstract

In the rapidly evolving landscape of online information dissemination, managing rumors has become an imperative challenge for governments worldwide. This study employs a tripartite evolutionary game model to examine the behavior evolution of the government, online media, and netizens in the process of rumor propagation under uncertain conditions. The innovation of the model lies in considering the probability of successful rumor detection under government regulation, the uncertainty of rumor dissemination by online media and netizens, and introducing a dynamic government penalty mechanism. Through simulation and analysis, we identify the evolutionarily stable strategies of each participant under different scenarios and provide specific governance strategies for each party involved. The results reveal that appropriate government penalties, proactive regulation by online media, and rational choices by netizens can effectively curb rumor spreading. In uncertain environments, adopting flexible policies and dynamic adjustment mechanisms is crucial for effective rumor governance. The results reveal that appropriate government penalties, proactive regulation by online media, and rational choices by netizens can effectively curb rumor spreading. In uncertain environments, adopting flexible policies and dynamic adjustment mechanisms is crucial for effective rumor governance. This study not only enriches the application of evolutionary game theory but also offers practical strategic recommendations for policymakers to address the challenges of rumor propagation.

Suggested Citation

  • Xuefan Dong & Lei Tang, 2025. "Rumor Governance Under Uncertain Conditions: An Evolutionary Game Theory Analysis," Annals of Data Science, Springer, vol. 12(3), pages 1073-1111, June.
  • Handle: RePEc:spr:aodasc:v:12:y:2025:i:3:d:10.1007_s40745-025-00606-y
    DOI: 10.1007/s40745-025-00606-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40745-025-00606-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40745-025-00606-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:aodasc:v:12:y:2025:i:3:d:10.1007_s40745-025-00606-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.