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

Generative Language Models Including ChatGPT (708) New Methods (1134) Violence including Domestic Violence/Abuse (157) Infoveillance and Social Listening (313) Peer-to-Peer Support and Online Communities (797) Information Seeking, Information Needs (561) Artificial Intelligence (2129)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65397, first published .
Classifying the Information Needs of Survivors of Domestic Violence in Online Health Communities Using Large Language Models: Prediction Model Development and Evaluation Study

Classifying the Information Needs of Survivors of Domestic Violence in Online Health Communities Using Large Language Models: Prediction Model Development and Evaluation Study

Classifying the Information Needs of Survivors of Domestic Violence in Online Health Communities Using Large Language Models: Prediction Model Development and Evaluation Study

Authors of this article:

Shaowei Guan1 Author Orcid Image ;   Vivian Hui2, 3 Author Orcid Image ;   Gregor Stiglic4 Author Orcid Image ;   Rose Eva Constantino3 Author Orcid Image ;   Young Ji Lee3 Author Orcid Image ;   Arkers Kwan Ching Wong5 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Guan S, Law N. A One-class variational autoencoder for smart contract vulnerability detection. International Journal of Information Security 2025;24(4) View
  2. Başaranoğlu M, Akbay E, Erdem E. From digital assistants to clinical partners: revolutionizing pediatric urology through large language model-powered decision support and patient education. World Journal of Urology 2025;43(1) View