Opening up echo chambers via optimal content recommendation
| Autor: | Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj |
|---|---|
| Přispěvatelé: | University College of London [London] (UCL), Institut National de Recherche en Informatique et en Automatique (Inria), Sorbonne Université (SU), Centre National de la Recherche Scientifique (CNRS), Networks and Performance Analysis (NPA), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), UK EPSRC grant EP/S022503/1, ANR FairEngine project under grant ANR-19-CE25-0011, ANR-19-CE25-0011,FairEngine,Ingénierie des plates-formes sociales équitables(2019), Vendeville, Antoine, Ingénierie des plates-formes sociales équitables - - FairEngine2019 - ANR-19-CE25-0011 - AAPG2019 - VALID |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences [INFO.INFO-SY] Computer Science [cs]/Systems and Control [cs.SY] social networks optimisation [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI] echo chambers Computer Science - Social and Information Networks Systems and Control (eess.SY) Electrical Engineering and Systems Science - Systems and Control [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI] recommendations FOS: Electrical engineering electronic engineering information engineering [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY] elections |
| Zdroj: | Proc. of the 11th International Conference on Complex Networks and their Applications The 11th International Conference on Complex Networks and their Applications (CNA'22) The 11th International Conference on Complex Networks and their Applications (CNA'22), Nov 2022, Palermo, Italy HAL |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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