ArticleJournal of medical Internet research2025
Public Attention to Mpox in China During the Pandemic: Qualitative Analysis of TikTok Data Using Latent Dirichlet Allocation Topic Modeling.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- YouTube Communication of the International Council of Nurses: A Topic Modeling Analysis Using Latent Dirichlet Allocation.International nursing review · 2026Article
- Cognitive differences and ethical concerns in artificial intelligence in healthcare: a comparative text mining study of public and healthcare professional discussions.BMC medical ethics · 2026Article
- Evaluating function availability and user satisfaction with nutrition apps: user-generated content analysis and text mining study.Nutrition journal · 2026Article
- From algorithmic efficiency to cascading health burdens: a text-mining study of online food delivery riders in the platform economy.Frontiers in public health · 2026Article
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Authors and funding
10 authors.
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Abstract
Background: Mpox has reemerged as a global public health concern. With the growing reliance on social media for health information dissemination, understanding public perception through these platforms is essential for designing effective health promotion strategies. Objective: This study analyzes TikTok data related to mpox using Latent Dirichlet Allocation (LDA) topic modeling. This paper aims to extract key topics and inform targeted health promotion strategies for mpox prevention and control. Methods: Using the "Aisou Jisou" system, we collected TikTok data containing the keyword "Mpox" from April 1, 2022, to March 31, 2025. The dataset comprised 25,672 text data and associated search terms. We analyzed trends in the Search Index and Target Group Index (TGI) across time, gender, age groups, and provinces. LDA topic modeling was applied to identify latent topics within the text data, and topic evolution was examined during 4 peak months of the Search Index. Results: A total of 4 major Search Index peaks were identified on TikTok in China, which are May 2022, July 2023, August 2024, and February 2025. These peaks aligned with key global and national mpox events, including WHO's declaration of a global mpox outbreak in May 2022 and the detection of the clade Ib Mpox in China in January 2025. TGI analysis revealed that users aged 18-23 years exhibited the highest engagement. Spatially, Beijing, Tianjin, and Jilin recorded the highest cumulative TGI values (5922.38, 5692.41, and 3579.90, respectively). LDA topic modeling identified 8 primary topics, including transmission and prevention, vaccine concerns, and misinformation, etc. Public attention evolved from general disease knowledge toward issues of stigmatization and vaccine distrust over time. Sankey diagrams illustrated shifts in public attention across topics at different Search Index peaks, with "Mpox Transmission and Prevention" receiving the most attention in May 2022 and "Mpox Vaccination and Infection Prevention" in February 2025. Conclusions: TikTok provides real-time insights into public attention during mpox outbreaks, but can also propagate misinformation and stigmatizing narratives. Public health authorities should leverage these platforms for timely communication, actively address misinformation, and mitigate social bias. Tailored strategies are needed to enhance health literacy, minimize stigma, and strengthen outbreak preparedness and response. This study highlights the dual role of social media as both an information source and a potential vector for misinformation, emphasizing the necessity for active monitoring and regulation by health authorities to ensure the accuracy and reliability of disseminated health information.
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