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

Emotional, Social, Psychological Support for Cancer (188) e-Mental Health and Cyberpsychology (1386) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Infodemiology and Infoveillance (1269) Peer-to-Peer Support and Online Communities (592) Breast Cancer (200) Natural Language Processing (636)

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 Tweetations (3) Metrics

Zhouqing Zhang   1 , ME ;   Kongmeng Liew   1, 2 , PhD ;   Roeline Kuijer   2 , PhD ;   Wan Jou She   1, 3 , PhD ;   Shuntaro Yada   1 , PhD ;   Shoko Wakamiya   1 , PhD ;   Eiji Aramaki   1 , PhD

1 Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan

2 School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand

3 Department of Information Science, Kyoto Institute of Technology, Kyoto, Japan

Corresponding Author: