IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i14p2253-d1699968.html
   My bibliography  Save this article

Optimal Media Control Strategy for Rumor Propagation in a Multilingual Dual Layer Reaction Diffusion Network Model

Author

Listed:
  • Guiyun Liu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
    These authors contributed equally to this work.)

  • Haozhe Xu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
    These authors contributed equally to this work.)

  • Yu Zhu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Yiyang Ma

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Zhipeng Chen

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

Abstract

The rapid advancement of Internet of Things technologies has significantly enhanced cross-regional communication among geographically and linguistically diverse populations on social platforms yet simultaneously accelerated the propagation of rumors across multilingual networks at unprecedented velocity. Therefore, this study focuses on investigating the spatiotemporal propagation dynamics and cross-lingual diffusion characteristics of rumors. Distinguished from conventional approaches, we innovatively formulate a hybrid dual-layer rumor containment model through a reaction–diffusion framework that explicitly incorporates the coupling control effects of media layers with independent propagation dynamics. Furthermore, we rigorously prove the differentiability of control-to-state mappings, which enables the derivation of necessary optimality conditions for the optimal control problem. Finally, comprehensive simulations validate both the adaptability and effectiveness of our media-based spatiotemporal control strategies in multilingual environments.

Suggested Citation

  • Guiyun Liu & Haozhe Xu & Yu Zhu & Yiyang Ma & Zhipeng Chen, 2025. "Optimal Media Control Strategy for Rumor Propagation in a Multilingual Dual Layer Reaction Diffusion Network Model," Mathematics, MDPI, vol. 13(14), pages 1-23, July.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:14:p:2253-:d:1699968
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/14/2253/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/14/2253/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jmathe:v:13:y:2025:i:14:p:2253-:d:1699968. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.