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Uncritical polarized groups: The impact of spreading fake news as fact in social networks

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  • San Martín, Jesús
  • Drubi, Fátima
  • Rodríguez Pérez, Daniel

Abstract

The spread of ideas in online social networks is a crucial phenomenon to understand nowadays the proliferation of fake news and their impact in democracies. This makes necessary to use models that mimic the circulation of rumors. The law of large numbers as well as the probability distribution of contact groups allow us to construct a model with a minimum number of hypotheses. Moreover, we can analyze with this model the presence of very polarized groups of individuals (humans or bots) who spread a rumor as soon as they know about it. Given only the initial number of individuals who know any news, in a population connected by an instant messaging application, we first deduce from our model a simple function of time to study the rumor propagation. We then prove that the polarized groups can be detected and quantified from empirical data. Finally, we also predict the time required by any rumor to reach a fixed percentage of the population.

Suggested Citation

  • San Martín, Jesús & Drubi, Fátima & Rodríguez Pérez, Daniel, 2020. "Uncritical polarized groups: The impact of spreading fake news as fact in social networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 192-206.
    • Handle: RePEc:eee:matcom:v:178:y:2020:i:c:p:192-206
    DOI: 10.1016/j.matcom.2020.06.013
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    References listed on IDEAS

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    1. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    2. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    3. Cheng Li & Zhiyong Zhang & Lanfang Zhang, 2018. "A Novel Authorization Scheme for Multimedia Social Networks Under Cloud Storage Method by Using MA-CP-ABE," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 8(3), pages 32-47, July.
    4. Sangeeta Gupta & Narsimha Gugulothu, 2018. "Secure NoSQL for the Social Networking and E-Commerce Based Bigdata Applications Deployed in Cloud," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 8(2), pages 113-129, April.
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    Cited by:

    1. Antonio Di Crescenzo & Paola Paraggio & Serena Spina, 2023. "Stochastic Growth Models for the Spreading of Fake News," Mathematics, MDPI, vol. 11(16), pages 1-23, August.

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