Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok
For researchers studying AI-generated content and platform dynamics, this paper provides empirical insights into the reception of AI narratives on social media, though the findings are preliminary and domain-specific.
The paper analyzes the 'history POV' trend on TikTok, where AI generates first-person historical scenes, finding a dominance of emotionally charged contemporary topics and historical inaccuracies. Holocaust content attracts disproportionately higher hate speech and disinformation.
This paper examines the history POV trend on TikTok, in which AI-generated first-person scenes depict historical events. We use a two-stage empirical approach: an exploratory pilot study and a larger-scale study building up on a dataset obtained through the TikTok Research API. In both studies we analyze the themes of the trend and how the audience responds in the comments. Findings show a dominance of emotionally charged contemporary history topics, with historical inaccuracies visible at the caption level. A comparative comment analysis of Black Death and Holocaust videos, combining manual annotation with DistilBERT-based classification, reveals that topic choice shapes audience response, with Holocaust content attracting disproportionately higher rates of hate speech and disinformation. The paper also reflects on the strengths and limitations of API-based research for studying fast-moving platform trends.