Analysing the Effect of Recommendation Algorithms on the Spread of Misinformation

Fernandez, Miriam; Bellogín, Alejandro and Cantador, Iván (2024). Analysing the Effect of Recommendation Algorithms on the Spread of Misinformation. In: Websci '24: 16th ACM Web Science Conference, 21-24 May 2024, Stuttgart, Germany, ACM, pp. 159–169.

DOI: https://doi.org/10.1145/3614419.3644003

Abstract

Recommendation algorithms (RAs) have been pointed out as one of the major culprits of misinformation spreading in the digital sphere.¹ However, it is still unclear how these algorithms propagate misinformation, e.g., which particular recommendation approaches are more prone to suggest misinforming items, or which internal parameters of the algorithms could be influencing more on their misinformation propagation capacity. Motivated by this fact, in this work, we present an analysis of the effect of some of the most popular recommendation algorithms on the spread of misinformation on Twitter (X). A set of guidelines on how to adapt these algorithms is provided based on such analysis and a comprehensive review of the research literature.

^{1 - Please note that amplifying, spreading and propagating are indistinctly used in this paper to refer to the amplifying effect that recommendation algorithms may have on misinformation when recommending or suggesting items to users.}

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