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

Formative Evaluation of Digital Health Interventions (3298) AI Language Models in Health Care (214) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2164) Natural Language Processing (931)

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 (4) Tweetations Metrics

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  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

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  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