IDEAS home Printed from https://ideas.repec.org/a/taf/tjorxx/v72y2021i12p2783-2803.html
   My bibliography  Save this article

Opinion dynamics based on infectious disease transmission model in the non-connected context of Pythagorean fuzzy trust relationship

Author

Listed:
  • Decui Liang
  • Bochun Yi
  • Zeshui Xu

Abstract

In a social network, people may express opinions and interact with others for a hot issue, in which the trust relationship plays an important role. For the determination of the trust relationship, there exists uncertainty, incomplete and non-connected challenges. In this article, we firstly introduce infectious disease transmission model to describe three types of people in a social network. Then, we propose an absorption law and the modified trust propagation and aggregation method to construct a complete connected social network. Furthermore, the improved DEMATEL method is designed to find the most influential people. In the process of opinion evolution, we consider the dynamic change of each people in three types through SIR model. Finally, we use a comprehensive experiment to illustrate our proposed algorithms. The experiment shows that our method can successfully describe the opinion evolution process and presents the flexibility of opinions.

Suggested Citation

  • Decui Liang & Bochun Yi & Zeshui Xu, 2021. "Opinion dynamics based on infectious disease transmission model in the non-connected context of Pythagorean fuzzy trust relationship," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(12), pages 2783-2803, December.
    • Handle: RePEc:taf:tjorxx:v:72:y:2021:i:12:p:2783-2803
    DOI: 10.1080/01605682.2020.1821585
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01605682.2020.1821585
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01605682.2020.1821585?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Jing & Liu, Yu & Liang, Decui & Tang, Maochun, 2023. "A new risk analysis approach to seek best production action during new product introduction," International Journal of Production Economics, Elsevier, vol. 262(C).

    More about this item

    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:taf:tjorxx:v:72:y:2021:i:12:p:2783-2803. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjor .

    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.