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

Theme Issue 2021: Health Natural Language Processing and Applications (16) Depression and Mood Disorders; Suicide Prevention (1392) Natural Language Processing (706) Machine Learning (1501)

Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28754, first published .
Depression Detection on Reddit With an Emotion-Based Attention Network: Algorithm Development and Validation

Depression Detection on Reddit With an Emotion-Based Attention Network: Algorithm Development and Validation

Depression Detection on Reddit With an Emotion-Based Attention Network: Algorithm Development and Validation

Authors of this article:

Lu Ren1 Author Orcid Image ;   Hongfei Lin1 Author Orcid Image ;   Bo Xu1, 2 Author Orcid Image ;   Shaowu Zhang1 Author Orcid Image ;   Liang Yang1 Author Orcid Image ;   Shichang Sun3 Author Orcid Image
Article Authors Cited by (42) Tweetations (3) Metrics

Journals

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  18. Liu J, Chen W, Wang L, Ding F. A hybrid depression detection model and correlation analysis for social media based on attention mechanism. International Journal of Machine Learning and Cybernetics 2024;15(7):2631 View
  19. Mieles Toloza I, Delgado Meza J, Acevedo-Suárez J. Análisis del Lenguaje Natural para la Identificación de Alteraciones Mentales en Redes Sociales: Una Revisión Sistemática de Estudios. Revista Politécnica 2024;53(1):57 View
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  25. Chen J, Liu S, Xu M, Wang P. Enhancing depression detection: A multimodal approach with text extension and content fusion. Expert Systems 2024;41(10) View
  26. Montejo-Ráez A, Molina-González M, Jiménez-Zafra S, García-Cumbreras M, García-López L. A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges. Computer Science Review 2024;53:100654 View
  27. van Buchem M, de Hond A, Fanconi C, Shah V, Schuessler M, Kant I, Steyerberg E, Hernandez-Boussard T. Applying natural language processing to patient messages to identify depression concerns in cancer patients. Journal of the American Medical Informatics Association 2024;31(10):2255 View
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Books/Policy Documents

  1. Dalal S, Jain S, Dave M. Proceedings of the International Health Informatics Conference. View
  2. Jickson S, Anoop V, Asharaf S. Proceedings of International Conference on Information Technology and Applications. View
  3. Zhu W, Zhang Y, Yu X, Lu M, Lin H. Health Information Processing. View