Study Maps Sentiment and Toxicity in Mental Health Content on TikTok During Awareness Month
Researchers analyzed nearly 28,000 TikTok videos and 80,000 comments posted during Mental Health Awareness Month in 2023 and 2024, finding that video content tends toward negative sentiment on emotionally charged topics while audience comments often shift toward more positive or mixed tones. The study used computational tools including BERTopic for topic modeling, XLM-T for sentiment analysis, and Detoxify for toxicity scoring to characterize how mental health discourse is framed and received. The findings offer a systematic, topic-level picture of how awareness campaigns play out on one of the world's most-used social platforms.
A preprint study posted to arXiv examined 28,341 TikTok videos and 80,130 comments collected during Mental Health Awareness Month (May) in 2023 and 2024 using the TikTok Research API. Researchers identified recurring themes spanning clinical conditions, emotional disclosure, self-care, and campaign-oriented content, with user engagement heavily concentrated in a small subset of topics. Sentiment in video content was frequently negative for emotionally charged subjects, while comments tended to be more mixed or positive — a pattern especially pronounced for suicide prevention content. Toxicity levels were generally low at the median, but comments showed longer-tailed outliers than videos, with elevated toxicity concentrated in specific topics such as 'Duet,' 'Suicide Prevention,' and 'Psychisch' (a German-language mental health term). The study treats video production and audience reception as distinct analytical layers, allowing comparisons between what creators post and how viewers respond. The authors note that engagement is highly skewed, meaning a small number of topics drive the majority of interactions during awareness campaigns.
What's missing
The study is a preprint and has not yet undergone peer review. It does not address whether the TikTok Research API sample is representative of all mental health content on the platform, nor does it account for algorithmic amplification that may shape which videos and comments are surfaced. The analysis is limited to text (transcriptions and comments) and does not capture visual or audio elements of videos, which may carry significant emotional content. Causal claims about TikTok's effects on mental health cannot be drawn from this observational design.
What different sources said
- arXiv physicsCenter
The Tone of Awareness: Topic, Sentiment, and Toxicity Maps During Mental Health Month on TikTok
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