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Fake News in Social Networks

Author

Listed:
  • Christoph Aymanns
  • Jakob Foerster
  • Co-Pierre Georg
  • Matthias Weber

Abstract

We propose multi-agent reinforcement learning as a new method for modeling fake news in social networks. This method allows us to model human behavior in social networks both in unaccustomed populations and in populations that have adapted to the presence of fake news. In particular the latter is challenging for existing methods. We find that a fake-news attack is more effective if it targets highly connected people and people with weaker private information. Attacks are more effective when the disinformation is spread across several agents than when the disinformation is concentrated with more intensity on fewer agents. Furthermore, fake news spread less well in balanced networks than in clustered networks. We test a part of our findings in a human-subject experiment. The experimental evidence provides support for the predictions from the model, suggesting that the model is suitable to analyze the spread of fake news in social networks.

Suggested Citation

  • Christoph Aymanns & Jakob Foerster & Co-Pierre Georg & Matthias Weber, 2017. "Fake News in Social Networks," Papers 1708.06233, arXiv.org, revised Oct 2025.
    • Handle: RePEc:arx:papers:1708.06233
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    References listed on IDEAS

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    1. Jadbabaie, Ali & Molavi, Pooya & Sandroni, Alvaro & Tahbaz-Salehi, Alireza, 2012. "Non-Bayesian social learning," Games and Economic Behavior, Elsevier, vol. 76(1), pages 210-225.
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    5. 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.
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    Cited by:

    1. Bertin Martens & Luis Aguiar & Estrella Gomez Herrera & Frank Muller, 2018. "The digital transformation of news media and the rise of disinformation and fake news," JRC Working Papers on Digital Economy 2018-02, Joint Research Centre.
    2. Bryan Fong, 2021. "Analysing the behavioural finance impact of 'fake news' phenomena on financial markets: a representative agent model and empirical validation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    3. Shimon Kogan & Tobias J Moskowitz & Marina Niessner, 2023. "Social Media and Financial News Manipulation," Review of Finance, European Finance Association, vol. 27(4), pages 1229-1268.

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