Examining AI-generated Historical Narratives and Their Reception through the Example of History POVs on TikTok

Arxiv: https://doi.org/10.48550/arXiv.2606.23300 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.