Published on in Vol 21 , No 5 (2019) :May

Proactive Suicide Prevention Online (PSPO): Machine Identification and Crisis Management for Chinese Social Media Users With Suicidal Thoughts and Behaviors

Proactive Suicide Prevention Online (PSPO): Machine Identification and Crisis Management for Chinese Social Media Users With Suicidal Thoughts and Behaviors

Proactive Suicide Prevention Online (PSPO): Machine Identification and Crisis Management for Chinese Social Media Users With Suicidal Thoughts and Behaviors

Journals

  1. Soron T, Shariful Islam S. Suicide on Facebook-the tales of unnoticed departure in Bangladesh. Global Mental Health 2020;7 View
  2. Liu J. Need to establish a new adolescent suicide prevention programme in South Korea. General Psychiatry 2020;33(4):e100200 View
  3. Liu X, Huang J, Yu N, Li Q, Zhu T. Mediation Effect of Suicide-Related Social Media Use Behaviors on the Association Between Suicidal Ideation and Suicide Attempt: Cross-Sectional Questionnaire Study. Journal of Medical Internet Research 2020;22(4):e14940 View
  4. Wang P, Yan Y, Si Y, Zhu G, Zhan X, Wang J, Pan R. Classification of Proactive Personality: Text Mining Based on Weibo Text and Short-Answer Questions Text. IEEE Access 2020;8:97370 View
  5. Teo A, Strange W, Bui R, Dobscha S, Ono S. Responses to Concerning Posts on Social Media and Their Implications for Suicide Prevention Training for Military Veterans: Qualitative Study. Journal of Medical Internet Research 2020;22(10):e22076 View
  6. Oh B, Yun J, Yeo E, Kim D, Kim J, Cho B. Prediction of Suicidal Ideation among Korean Adults Using Machine Learning: A Cross-Sectional Study. Psychiatry Investigation 2020;17(4):331 View
  7. Figueroa Saavedra C, Otzen Hernández T, Alarcón Godoy C, Ríos Pérez A, Frugone Salinas D, Lagos Hernández R. Association between suicidal ideation and acoustic parameters of university students’ voice and speech: a pilot study. Logopedics Phoniatrics Vocology 2021;46(2):55 View
  8. Castillo-Sánchez G, Marques G, Dorronzoro E, Rivera-Romero O, Franco-Martín M, De la Torre-Díez I. Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review. Journal of Medical Systems 2020;44(12) View
  9. Sarsam S, Al-Samarraie H, Alzahrani A, Alnumay W, Smith A. A lexicon-based approach to detecting suicide-related messages on Twitter. Biomedical Signal Processing and Control 2021;65:102355 View
  10. Hazaa Y, Almaqtari F, Al-Swidi A, Tan A. Factors Influencing Crisis Management: A systematic review and synthesis for future research. Cogent Business & Management 2021;8(1):1878979 View
  11. Ji S, Pan S, Li X, Cambria E, Long G, Huang Z. Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. IEEE Transactions on Computational Social Systems 2021;8(1):214 View
  12. Stirling E, Willcox J, Ong K, Forsyth A. Social media analytics in nutrition research: a rapid review of current usage in investigation of dietary behaviours. Public Health Nutrition 2021;24(6):1193 View
  13. Chen J, Wang Y. Social Media Use for Health Purposes: Systematic Review. Journal of Medical Internet Research 2021;23(5):e17917 View
  14. Liu X, Liu X. Online Suicide Identification in the Framework of Rhetorical Structure Theory (RST). Healthcare 2021;9(7):847 View

Books/Policy Documents

  1. Cheng X, Wang X, Ouyang T, Feng Z. Neurological and Mental Disorders. View
  2. Huang Y, Liu X, Zhu T. Human Centered Computing. View
  3. Sinha N. Enhanced Telemedicine and e-Health. View
  4. Chanda K, Ghosh A, Dey S, Bose R, Roy S. Smart IoT for Research and Industry. View