IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v35y2024i12ns0129183124501511.html
   My bibliography  Save this article

Kinetic modeling of a Sznajd opinion model on social networks

Author

Listed:
  • Jie Liao

    (School of Mathematics, Shanghai University of Finance and Economics, Shanghai 200433, P. R. China)

  • Xiongfeng Yang

    (School of Mathematical Sciences, CMA-Shanghai and MOE-LSC, Shanghai Jiao Tong University, Shanghai 200240, P. R. China)

Abstract

In this paper, we study a kinetic modeling of opinion formation on social networks in which the distribution function depends on both the opinion and the connectivity of the agents. The opinion exchange process is governed by a Sznajd-type model with three opinions, ±1, 0, and the social network is represented statistically with connectivity denoting the number of contacts of a given individual. It is commonly accepted that, in social networks, the opinion of the agents with a higher connectivity, i.e. a larger number of followers, is more convincing than that of the agents with a lower number of followers. By the kinetic modeling approach, we derived the asymptotic mean opinion of a social network in terms of the initial opinion and the connectivity of the agents. The present work extends the result in [N. Loy, M. Raviola and A. Tosin, Opinion polarisation in social networks, Phil. Trans. R. Soc. A 380, 20210158 (2021)] where only binary opinions, ±1, were considered, that indecisive people who cannot make a clear choice between ±1 are allowed in this study.

Suggested Citation

  • Jie Liao & Xiongfeng Yang, 2024. "Kinetic modeling of a Sznajd opinion model on social networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 35(12), pages 1-22, December.
    • Handle: RePEc:wsi:ijmpcx:v:35:y:2024:i:12:n:s0129183124501511
    DOI: 10.1142/S0129183124501511
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0129183124501511
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0129183124501511?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:wsi:ijmpcx:v:35:y:2024:i:12:n:s0129183124501511. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    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.