Published on in Vol 6, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35563, first published .
Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study

Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study

Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study

Authors of this article:

Cecilia Lao1 Author Orcid Image ;   Jo Lane2 Author Orcid Image ;   Hanna Suominen1, 3 Author Orcid Image

Journals

  1. Fu J, Li C, Zhou C, Li W, Lai J, Deng S, Zhang Y, Guo Z, Wu Y. Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review. Journal of Medical Internet Research 2023;25:e43349 View
  2. Pei Y, O'Brien K. Use of Social Media Data Mining to Examine Needs, Concerns, and Experiences of People With Traumatic Brain Injury. American Journal of Speech-Language Pathology 2024;33(2):831 View
  3. Khan A, Ali R. Unraveling minds in the digital era: a review on mapping mental health disorders through machine learning techniques using online social media. Social Network Analysis and Mining 2024;14(1) View
  4. Atmakuru A, Shahini A, Chakraborty S, Seoni S, Salvi M, Hafeez-Baig A, Rashid S, Tan R, Barua P, Molinari F, Acharya U. Artificial intelligence-based suicide prevention and prediction: A systematic review (2019–2023). Information Fusion 2025;114:102673 View
  5. Thomas J, Lucht A, Segler J, Wundrack R, Miché M, Lieb R, Kuchinke L, Meinlschmidt G. An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study. JMIR Public Health and Surveillance 2025;11:e63809 View
  6. Campbell L, Frawley C, Lambie G, Cabrera K, Vizcarra B. Examining Artificial Intelligence Policies in Counsellor Education. Counselling and Psychotherapy Research 2025;25(1) View
  7. McBride L, Badal V, Harvey P, Pinkham A, Aich A, Parde N, Depp C. Evaluating natural language processing derived linguistic features associated with current suicidal ideation, past attempts, and future suicidal behavior. Journal of Psychiatric Research 2025;187:25 View

Books/Policy Documents

  1. Sazzed S. Social, Cultural, and Behavioral Modeling. View

Conference Proceedings

  1. Wang Y, Zhang G, Zhang S, Sun Y, Jiang B. Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023). A study on suicidal ideation detection based on domain knowledge and multi-head knowledge attention mechanism View
  2. Mayahi A, Alshatti E. 2023 Computer Applications & Technological Solutions (CATS). Assessing English Language Writing and Readability Skills using Long Short-Term Memory Model View
  3. Sazzed S. 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Unraveling Affective Responses and Core Determinants in Health and Trauma-Driven Suicidal Narratives View