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[working paper]

dc.contributor.authorWedel, Lionde
dc.contributor.authorPfiffner, Nicode
dc.contributor.authorOhme, Jakobde
dc.contributor.authorFriemel, Thomas N.de
dc.contributor.authorGaisbauer, Felixde
dc.contributor.authorLehner, Marcode
dc.contributor.authorSchöffel, Robertde
dc.contributor.authorKoenigsdorff, Simonde
dc.contributor.authorPlavec, Jan Georgde
dc.contributor.authorWolf, Julikade
dc.date.accessioned2026-03-09T11:15:50Z
dc.date.available2026-03-09T11:15:50Z
dc.date.issued2026de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/108733
dc.description.abstractThe impact of TikTok on recent elections around the globe has been a significant topic of public discourse, including debates over banning the platform (US) or regulating it (EU), specifically the possibility of asymmetric algorithmic amplification of certain political content by "the TikTok algorithm". By using digital traces of 624 participants’ watch histories collected through data donations, this study provides large-scale insights into the content voters have been exposed to during the German Federal Election campaign in 2025. We explore the prevalence of political content from official party accounts, political influencers, traditional news accounts, and party-referencing content in TikTok Feeds during the German Federal Election 2025. Overall, political content makes up on average 5% of videos in user watch histories in the two months prior to elections with an increase closer to election date - while the share of legacy news stays constant around 1% throughout the whole time period. We do not find clear evidence for asymmetric algorithmic curation of extreme political content. Instead, our findings indicate that most of the political content users see on TikTok aligns with their stated political preferences and we cannot observe a disproportional prevalence of populist or right-wing content.de
dc.languageende
dc.subject.ddcPublizistische Medien, Journalismus,Verlagswesende
dc.subject.ddcNews media, journalism, publishingen
dc.subject.otherTikTok; content exposure; algorithmic selection; recommender systems; German Federal Election 2025; data donationde
dc.titlePolitical content and news exposure of German TikTok users during the 2025 Federal German Electionsde
dc.description.reviewnicht begutachtetde
dc.description.reviewnot revieweden
dc.publisher.countryDEUde
dc.subject.classozinteraktive, elektronische Mediende
dc.subject.classozInteractive, electronic Mediaen
dc.subject.classozWirkungsforschung, Rezipientenforschungde
dc.subject.classozImpact Research, Recipient Researchen
dc.subject.thesozSoziale Mediende
dc.subject.thesozsocial mediaen
dc.subject.thesozAlgorithmusde
dc.subject.thesozalgorithmen
dc.subject.thesozpolitischer Einflussde
dc.subject.thesozpolitical influenceen
dc.subject.thesozWahlverhaltende
dc.subject.thesozvoting behavioren
dc.subject.thesozBundestagswahlde
dc.subject.thesozelection to the Bundestagen
dc.identifier.urnurn:nbn:de:0168-ssoar-108733-2
dc.rights.licenceCreative Commons - Namensnennung, Nicht kommerz., Keine Bearbeitung 4.0de
dc.rights.licenceCreative Commons - Attribution-Noncommercial-No Derivative Works 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10094228
internal.identifier.thesoz10035039
internal.identifier.thesoz10041597
internal.identifier.thesoz10061173
internal.identifier.thesoz10040137
dc.type.stockmonographde
dc.type.documentArbeitspapierde
dc.type.documentworking paperen
dc.source.pageinfo43de
internal.identifier.classoz1080404
internal.identifier.classoz1080407
internal.identifier.document3
internal.identifier.ddc070
dc.description.pubstatusPreprintde
dc.description.pubstatusPreprinten
internal.identifier.licence20
internal.identifier.pubstatus3
internal.identifier.review3
dc.subject.classhort10100de
dc.subject.classhort10800de
dc.subject.classhort10500de
dc.subject.classhort29900de
dc.subject.classhort20800de
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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