This paper is in the following e-collection/theme issue:

Infodemiology and Infoveillance (1558) Patient Education for Cancer (227) Information Seeking, Information Needs (561) Information Quality in Digital Media (407) Cancer and Prevention in the Media (43) Cancer Epidemiology, Cancer Surveillance and Infodemiology (113)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55937, first published .
Cancer Prevention and Treatment on Chinese Social Media: Machine Learning–Based Content Analysis Study

Cancer Prevention and Treatment on Chinese Social Media: Machine Learning–Based Content Analysis Study

Cancer Prevention and Treatment on Chinese Social Media: Machine Learning–Based Content Analysis Study

Authors of this article:

Keyang Zhao1 Author Orcid Image ;   Xiaojing Li1, 2 Author Orcid Image ;   Jingyang Li3 Author Orcid Image
Article Authors Cited by (5) Tweetations Metrics

Journals

  1. Zitu M, Le T, Duong T, Haddadan S, Garcia M, Amorrortu R, Zhao Y, Rollison D, Thieu T. Large language models in cancer: potentials, risks, and safeguards. BJR|Artificial Intelligence 2025;2(1) View
  2. Lai Y, Ye J, Newcombe K, Zhao X. Empowering Unvaccinated Women with Information: How Online Cancer Information Seeking and Scanning Encourage HPV Vaccination in China. Health Communication 2025;40(14):2985 View
  3. Donskova Y, Kurilova A, Zhang Y. Strategies and Tactics of Medical Social Advertising for Prevention and Treatment of Oncological Diseases. Nauchnyi dialog 2025;14(4):231 View
  4. Duan Y, Chen Y, Sun Q, Chen J, Zhang J, Yun B, Cai T, Yuan C. Characterizing authoritative oncology-related key opinion leaders on Weibo: A social media profiling study. Asia-Pacific Journal of Oncology Nursing 2025;12:100742 View
  5. Xie Y, Guo Z, Zeng X, Zhai D, Zhai G, Feng Y, Huang H. Social Media–Based Cancer Education: Bibliometric and Thematic Analysis. JMIR Cancer 2025;11:e77214 View