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

Emotional, Social, Psychological Support for Cancer (223) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1886) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1820) Infodemiology and Infoveillance (1483) Peer-to-Peer Support and Online Communities (740) Breast Cancer (255) Natural Language Processing (828)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51332, first published .
Differing Content and Language Based on Poster-Patient Relationships on the Chinese Social Media Platform Weibo: Text Classification, Sentiment Analysis, and Topic Modeling of Posts on Breast Cancer

Differing Content and Language Based on Poster-Patient Relationships on the Chinese Social Media Platform Weibo: Text Classification, Sentiment Analysis, and Topic Modeling of Posts on Breast Cancer

Differing Content and Language Based on Poster-Patient Relationships on the Chinese Social Media Platform Weibo: Text Classification, Sentiment Analysis, and Topic Modeling of Posts on Breast Cancer

Authors of this article:

Zhouqing Zhang1 Author Orcid Image ;   Kongmeng Liew1, 2 Author Orcid Image ;   Roeline Kuijer2 Author Orcid Image ;   Wan Jou She1, 3 Author Orcid Image ;   Shuntaro Yada1 Author Orcid Image ;   Shoko Wakamiya1 Author Orcid Image ;   Eiji Aramaki1 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

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  3. Shankar R, Yip A. Sentiment analysis and topic modeling of social media data to explore public discourse on irritable bowel syndrome. Scientific Reports 2025;15(1) View