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dc.contributor.authorMartínez-Durive, Orlando E. 
dc.contributor.authorUcar, Iñaki
dc.contributor.authorSmoreda, Zbigniew
dc.contributor.authorMoro, Esteban
dc.contributor.authorFiore, Marco 
dc.date.accessioned2026-09-11T15:40:57Z
dc.date.available2026-09-11T15:40:57Z
dc.date.issued2026-10-12
dc.identifier.urihttps://hdl.handle.net/20.500.12761/2070
dc.description.abstractUnderstanding how digital platform consumption relates to political alignment is paramount in contemporary democracies, yet large-scale observational evidence spanning multiple platforms and elections remains scarce. We analyze passive mobile network metadata from a major French mobile network operator (MNO) covering approximately 31% of the mobile market across urban and suburban areas of metropolitan France during the 2019 and 2024 European Parliament elections. Integrating demands for tens of mobile services, including social media, news, messaging, and streaming, with socioeconomic indicators, we model vote shares via Dirichlet regression. We find that digital consumption provides independent and complementary signals of political alignment that, for several parties, match or exceed the predictive power of traditional socioeconomic indicators; combining both increases explanatory ability by up to 28.23%. For instance, right-wing support is associated with higher consumption of Facebook and TikTok, whereas engagement with online news outlets, Twitter, and Instagram correlates with centrist and progressive vote. These associations are consistent across 2019 and 2024, providing a population-scale view of the relationship between mobile platform use and political alignment.es
dc.description.sponsorshipFrench National Research Agency (ANR)es
dc.language.isoenges
dc.titleDigital Consumption and Political Alignment: Evidence from Mobile Data Across Two European Elections in Francees
dc.typeconference objectes
dc.conference.date12-16 October 2026es
dc.conference.placeKarlsruhe, Germanyes
dc.conference.titleInternet Measurement Conference *
dc.event.typeconferencees
dc.pres.typepaperes
dc.type.hasVersionVoRes
dc.rights.accessRightsopen accesses
dc.acronymIMC*
dc.rankA*
dc.relation.projectIDANR-22-CE25-0016es
dc.relation.projectNameCoCo5G (Traffic Collection, Contextual Analysis, Data-driven Optimization for 5G)es
dc.subject.keywordnetwork measurementes
dc.subject.keywordmobile networkses
dc.subject.keyworddigital consumptiones
dc.subject.keywordpolitical alignmentes
dc.subject.keywordelectionses
dc.subject.keywordDirichlet regressiones
dc.description.refereedTRUEes
dc.description.statusinpresses


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