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Mathematical models for fake news

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  • Dorje C. Brody
  • David M. Meier

Abstract

Over the past decade it has become evident that intentional disinformation in the political context -- so-called fake news -- is a danger to democracy. However, until now there has been no clear understanding of how to define fake news, much less how to model it. This paper addresses both of these issues. A definition of fake news is given, and two approaches for the modelling of fake news and its impact in elections and referendums are introduced. The first approach, based on the idea of a representative voter, is shown to be suitable for obtaining a qualitative understanding of phenomena associated with fake news at a macroscopic level. The second approach, based on the idea of an election microstructure, describes the collective behaviour of the electorate by modelling the preferences of individual voters. It is shown through a simulation study that the mere knowledge that fake news may be in circulation goes a long way towards mitigating the impact of fake news.

Suggested Citation

  • Dorje C. Brody & David M. Meier, 2018. "Mathematical models for fake news," Papers 1809.00964, arXiv.org, revised Nov 2021.
    • Handle: RePEc:arx:papers:1809.00964
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    Cited by:

    1. Raffaele D’Ambrosio & Giuseppe Giordano & Serena Mottola & Beatrice Paternoster, 2021. "Stiffness Analysis to Predict the Spread Out of Fake Information," Future Internet, MDPI, vol. 13(9), pages 1-10, August.

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