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Political content and news exposure of German TikTok users during the 2025 Federal German Elections
[working paper]
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... view more
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.... view less
Keywords
social media; algorithm; political influence; voting behavior; election to the Bundestag
Classification
Interactive, electronic Media
Impact Research, Recipient Research
Free Keywords
TikTok; content exposure; algorithmic selection; recommender systems; German Federal Election 2025; data donation
Document language
English
Publication Year
2026
Page/Pages
43 p.
Status
Preprint; not reviewed
Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0