{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T12:38:05Z","timestamp":1792067885264,"version":"4.4.0"},"reference-count":50,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using the \u201cAisou Jisou\u201d system, we collected TikTok data containing the keyword \u201cMpox\u201d 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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\u2019s 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\u201023 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 \u201cMpox Transmission and Prevention\u201d receiving the most attention in May 2022 and \u201cMpox Vaccination and Infection Prevention\u201d in February 2025.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/77424","type":"journal-article","created":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T09:22:05Z","timestamp":1756459325000},"page":"e77424-e77424","source":"Crossref","is-referenced-by-count":10,"title":["Public Attention to Mpox in China During the Pandemic: Qualitative Analysis of TikTok Data Using Latent Dirichlet Allocation Topic Modeling"],"prefix":"10.2196","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1282-1797","authenticated-orcid":false,"given":"DongHang","family":"Luo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8433-505X","authenticated-orcid":false,"given":"Jie","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0650-136X","authenticated-orcid":false,"given":"Yaoyao","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9978-7146","authenticated-orcid":false,"given":"Mengnan","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7936-3610","authenticated-orcid":false,"given":"Yaping","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0544-1943","authenticated-orcid":false,"given":"Lin","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0324-3537","authenticated-orcid":false,"given":"Jing","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8036-9125","authenticated-orcid":false,"given":"Wei","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3148-6601","authenticated-orcid":false,"given":"Wei","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9423-1250","authenticated-orcid":false,"given":"Chu","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,8,21]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","first-page":"8","DOI":"10.3390\/tropicalmed1010008","article-title":"Human monkeypox: current state of knowledge and implications for the future","volume":"1","author":"Brown","journal-title":"TropicalMed"},{"issue":"1","key":"R2","doi-asserted-by":"publisher","DOI":"10.1038\/s41392-023-01675-2","article-title":"Mpox (formerly monkeypox): pathogenesis, prevention and treatment","volume":"8","author":"Lu","journal-title":"Sig Transduct Target Ther"},{"key":"R3","unstructured":"Mpox - Democratic Republic of the Congo. 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