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

Formative Evaluation of Digital Health Interventions (3278) AI Language Models in Health Care (209) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2148) Natural Language Processing (924)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60286, first published .
Psychological and Behavioral Insights From Social Media Users: Natural Language Processing–Based Quantitative Study on Mental Well-Being

Psychological and Behavioral Insights From Social Media Users: Natural Language Processing–Based Quantitative Study on Mental Well-Being

Psychological and Behavioral Insights From Social Media Users: Natural Language Processing–Based Quantitative Study on Mental Well-Being

Authors of this article:

Xingwei Yang1 Author Orcid Image ;   Guang Li2 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Masur L, Driller M, Suppiah H, Matzka M, Sperlich B, Düking P. Assessment of Recommendations Provided to Athletes Regarding Sleep Education by GPT-4o and Google Gemini: Comparative Evaluation Study. JMIR Formative Research 2025;9:e71358 View
  2. Zheng H, Zhang X. Psychiatry in the age of AI: transforming theory, practice, and medical education. Frontiers in Public Health 2025;13 View

Conference Proceedings

  1. Immanuel C, Cindyana , Cyrilla V, Meyliana . 2025 International Conference on Information Technology Research and Innovation (ICITRI). The Role of AI in Detecting and Predicting Mental Health Crises in Social Media View