IDEAS home Printed from https://ideas.repec.org/a/eee/jeborg/v231y2025ics0167268125000113.html
   My bibliography  Save this article

Disinformation in group chat social media network

Author

Listed:
  • Shan, Yaping

Abstract

This paper introduces a model exploring disinformation propagation within group chat social media networks and its sway on public opinions. The model highlights the observation that disinformation disseminators not only distribute misleading content to sway undecided individuals but also engage in a learning process to augment their influence. Undecided agents form divergent long-term opinions influenced by both their direct exposure to disinformation and their interactions within the social network. Identifying the key influencers in the network becomes crucial in mitigating the impact of disinformation. This study proposes novel centrality measures to pinpoint these influencers, providing social media companies with effective strategies to mitigate the impact of disinformation on their platforms.

Suggested Citation

  • Shan, Yaping, 2025. "Disinformation in group chat social media network," Journal of Economic Behavior & Organization, Elsevier, vol. 231(C).
  • Handle: RePEc:eee:jeborg:v:231:y:2025:i:c:s0167268125000113
    DOI: 10.1016/j.jebo.2025.106891
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167268125000113
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jebo.2025.106891?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.

    References listed on IDEAS

    as
    1. Francis Bloch & Matthew O. Jackson & Pietro Tebaldi, 2023. "Centrality measures in networks," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 61(2), pages 413-453, August.
    2. Acemoglu, Daron & Ozdaglar, Asuman & ParandehGheibi, Ali, 2010. "Spread of (mis)information in social networks," Games and Economic Behavior, Elsevier, vol. 70(2), pages 194-227, November.
    3. Matthew O. Jackson, 2020. "A typology of social capital and associated network measures," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 54(2), pages 311-336, March.
    4. Daron Acemoğlu & Giacomo Como & Fabio Fagnani & Asuman Ozdaglar, 2013. "Opinion Fluctuations and Disagreement in Social Networks," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 1-27, February.
    5. Abhijit Banerjee & Arun G Chandrasekhar & Esther Duflo & Matthew O Jackson, 2019. "Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(6), pages 2453-2490.
    6. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    7. Neil F. Johnson & Nicolas Velásquez & Nicholas Johnson Restrepo & Rhys Leahy & Nicholas Gabriel & Sara El Oud & Minzhang Zheng & Pedro Manrique & Stefan Wuchty & Yonatan Lupu, 2020. "The online competition between pro- and anti-vaccination views," Nature, Nature, vol. 582(7811), pages 230-233, June.
    8. Philipp Lorenz-Spreen & Bjarke Mørch Mønsted & Philipp Hövel & Sune Lehmann, 2019. "Accelerating dynamics of collective attention," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Della Lena, Sebastiano, 2024. "The spread of misinformation in networks with individual and social learning," European Economic Review, Elsevier, vol. 168(C).
    2. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    3. Amir, Gideon & Arieli, Itai & Ashkenazi-Golan, Galit & Peretz, Ron, 2025. "Granular DeGroot dynamics – A model for robust naive learning in social networks," Journal of Economic Theory, Elsevier, vol. 223(C).
    4. Buechel, Berno & Klößner, Stefan & Meng, Fanyuan & Nassar, Anis, 2023. "Misinformation due to asymmetric information sharing," Journal of Economic Dynamics and Control, Elsevier, vol. 150(C).
    5. Prummer, Anja & Siedlarek, Jan-Peter, 2017. "Community leaders and the preservation of cultural traits," Journal of Economic Theory, Elsevier, vol. 168(C), pages 143-176.
    6. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska, 2023. "On the Design of Public Debate in Social Networks," Operations Research, INFORMS, vol. 71(2), pages 626-648, March.
    7. Azzimonti, Marina & Fernandes, Marcos, 2023. "Social media networks, fake news, and polarization," European Journal of Political Economy, Elsevier, vol. 76(C).
    8. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2015. "Strategic influence in social networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01158168, HAL.
    9. Eger, Steffen, 2016. "Opinion dynamics and wisdom under out-group discrimination," Mathematical Social Sciences, Elsevier, vol. 80(C), pages 97-107.
    10. Matjaž Steinbacher & Mitja Steinbacher, 2019. "Opinion Formation with Imperfect Agents as an Evolutionary Process," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 479-505, February.
    11. Ding, Huihui & Pivato, Marcus, 2021. "Deliberation and epistemic democracy," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 138-167.
    12. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska, 2022. "On the design of public debate in social networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03770884, HAL.
    13. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska, 2022. "On the design of public debate in social networks," Post-Print hal-03770884, HAL.
    14. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska, 2022. "On the design of public debate in social networks," PSE-Ecole d'économie de Paris (Postprint) hal-03770884, HAL.
    15. Foerster, Manuel, 2018. "Finite languages, persuasion bias, and opinion fluctuations," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 46-57.
    16. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    17. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    18. Francesco Drago & Friederike Mengel & Christian Traxler, 2020. "Compliance Behavior in Networks: Evidence from a Field Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 96-133, April.
    19. Foerster, Manuel, 2019. "Dynamics of strategic information transmission in social networks," Theoretical Economics, Econometric Society, vol. 14(1), January.
    20. Marina Azzimonti-Renzo & Alessandra Fogli & Fabrizio Perri & Mark Ponder, 2020. "Pandemic Control in ECON-EPI Networks," Staff Report 609, Federal Reserve Bank of Minneapolis.

    More about this item

    Keywords

    Disinformation; Social media network; Network centrality;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    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:eee:jeborg:v:231:y:2025:i:c:s0167268125000113. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jebo .

    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.