BWL XI: Paper in EPJ Data Science
A new research paper studying political communication on TikTok has been accepted for publication in EPJ Data Science.
Title: Engagement with political videos on TikTok during the 2025 German federal election
Authors: Kirill Solovev, Chiara Drolsbach, Emma Demirel, Nicolas Pröllochs
Abstract:
Short-form video platforms like TikTok reshape how politicians communicate and have become important tools for electoral campaigning. Yet it remains unclear what kinds of political messages gain traction in these fast-paced, algorithmically curated environments, which are particularly popular among younger audiences. In this study, we use computational content analysis to analyze a comprehensive dataset of N= 25,292 TikTok videos posted by German politicians in the run-up to the 2025 German federal election. Our empirical analysis shows that videos expressing negative emotions (e.g., anger, disgust) and outgroup animosity were significantly more likely to generate engagement than those emphasizing positive emotion, relatability, or identity. Furthermore, ideologically extreme parties (on both sides of the political spectrum) were both more likely to post this type of content and more successful in generating engagement than centrist parties. Taken together, these findings suggest that divisive political communication tends to receive higher engagement than unifying messages on TikTok, thereby potentially benefiting extreme actors who are more inclined to capitalize on this logic.
Paper available here (open access)