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https://nbn-resolving.org/urn:nbn:de:0168-ssoar-108733-2
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Political content and news exposure of German TikTok users during the 2025 Federal German Elections
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Abstract The 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 algorit... mehr
The 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.... weniger
Thesaurusschlagwörter
Soziale Medien; Algorithmus; politischer Einfluss; Wahlverhalten; Bundestagswahl
Klassifikation
interaktive, elektronische Medien
Wirkungsforschung, Rezipientenforschung
Freie Schlagwörter
TikTok; content exposure; algorithmic selection; recommender systems; German Federal Election 2025; data donation
Sprache Dokument
Englisch
Publikationsjahr
2026
Seitenangabe
43 S.
Status
Preprint; nicht begutachtet
Lizenz
Creative Commons - Namensnennung, Nicht kommerz., Keine Bearbeitung 4.0