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2023 | OriginalPaper | Buchkapitel

Opening up Echo Chambers via Optimal Content Recommendation

verfasst von : Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj

Erschienen in: Complex Networks and Their Applications XI

Verlag: Springer International Publishing

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Abstract

Online social platforms have become central in the political debate. In this context, the existence of echo chambers is a problem of primary relevance. These clusters of like-minded individuals tend to reinforce prior beliefs, elicit animosity towards others and aggravate the spread of misinformation. We study this phenomenon on a Twitter dataset related to the 2017 French presidential elections and propose a method to tackle it with content recommendations. We use a quadratic program to find optimal recommendations that maximise the diversity of content users are exposed to, while still accounting for their preferences. Our method relies on a theoretical model that can sufficiently describe how content flows through the platform. We show that the model provides good approximations of empirical measures and demonstrate the effectiveness of the optimisation algorithm at mitigating the echo chamber effect on this dataset, even with limited budget for recommendations.

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Fußnoten
1
Differently distributed times induce similar equilibrium behaviour [8].
 
2
Other selection and eviction policies induce similar equilibrium behaviour [8].
 
3
Certain contexts might actually benefit from this simplification. For example mentions and replies on Twitter may sometimes represent support and sometimes hostility towards the initial content [22].
 
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Metadaten
Titel
Opening up Echo Chambers via Optimal Content Recommendation
verfasst von
Antoine Vendeville
Anastasios Giovanidis
Effrosyni Papanastasiou
Benjamin Guedj
Copyright-Jahr
2023
DOI
https://doi.org/10.1007/978-3-031-21127-0_7

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