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

Clinical Information and Decision Making (1917) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1913) Peer-to-Peer Support and Online Communities (798) Infodemiology and Infoveillance (1560) Participatory Cancer Care (119) Patient Education for Cancer (227) Machine Learning (2077) Natural Language Processing (917) Chemotherapy and Side Effects Management (110) Doctor-Patient Communication on Cancer, Prevention, and Screening (78) Emotional, Social, Psychological Support for Cancer (250)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60948, first published .
Perceptions in 3.6 Million Web-Based Posts of Online Communities on the Use of Cancer Immunotherapy: Data Mining Using BERTopic

Perceptions in 3.6 Million Web-Based Posts of Online Communities on the Use of Cancer Immunotherapy: Data Mining Using BERTopic

Perceptions in 3.6 Million Web-Based Posts of Online Communities on the Use of Cancer Immunotherapy: Data Mining Using BERTopic

Authors of this article:

Xingyue Wu1 Author Orcid Image ;   Chun Sing Lam1 Author Orcid Image ;   Ka Ho Hui1 Author Orcid Image ;   Herbert Ho-fung Loong2 Author Orcid Image ;   Keary Rui Zhou1 Author Orcid Image ;   Chun-Kit Ngan3 Author Orcid Image ;   Yin Ting Cheung1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. de-Marcos L, Domínguez-Díaz A. LLM-Based Topic Modeling for Dark Web Q&A Forums: A Comparative Analysis With Traditional Methods. IEEE Access 2025;13:67159 View
  2. Chatzimina M, Papadaki H, Pontikoglou C, Tsiknakis M. Topic modeling and sentiment analysis of Greek clinician–patient conversations in hematologic malignancies. International Journal of Medical Informatics 2025;204:106071 View
  3. De-Marcos L, Domínguez-Díaz A, Stapic Z. What’s Going On in Dark Web Question and Answer Forums: Topic Diversity and Linguistic Characteristics. IEEE Access 2025;13:149880 View