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Citing this Article

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Published on 10.07.17 in Vol 19, No 7 (2017): July

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

Works citing "Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.7276):

(note that this is only a small subset of citations)

  1. Lopez‐Castroman J, Moulahi B, Azé J, Bringay S, Deninotti J, Guillaume S, Baca‐Garcia E. Mining social networks to improve suicide prevention: A scoping review. Journal of Neuroscience Research 2020;98(4):616
    CrossRef
  2. Giuntini FT, Cazzolato MT, dos Reis MDJD, Campbell AT, Traina AJM, Ueyama J. A review on recognizing depression in social networks: challenges and opportunities. Journal of Ambient Intelligence and Humanized Computing 2020;
    CrossRef
  3. Zheng Z, Yang Q, Liu Z, Qiu J, Gu J, Hao Y, Song C, Jia Z, Hao C. Association of Aftfective States with Sexual Behavior and Health Status Among Men Who Have Sex With Men in China: Exploratory Study Using Social Media Data. Journal of Medical Internet Research 2020;22(1):e13201
    CrossRef
  4. Burke TA, Ammerman BA, Jacobucci R. The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review. Journal of Affective Disorders 2019;245:869
    CrossRef
  5. Gooding P. Mapping the rise of digital mental health technologies: Emerging issues for law and society. International Journal of Law and Psychiatry 2019;67:101498
    CrossRef
  6. Fonseka TM, Bhat V, Kennedy SH. The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors. Australian & New Zealand Journal of Psychiatry 2019;53(10):954
    CrossRef
  7. Lee K, Lee D, Hong HJ. Text mining analysis of teachers’ reports on student suicide in South Korea. European Child & Adolescent Psychiatry 2019;
    CrossRef
  8. Asongu S, Nwachukwu J, Orim S, Pyke C. Crime and social media. Information Technology & People 2019;32(5):1215
    CrossRef
  9. Van den Nest M, Till B, Niederkrotenthaler T. Comparing Indicators of Suicidality Among Users in Different Types of Nonprofessional Suicide Message Boards. Crisis 2019;40(2):125
    CrossRef
  10. Chen L, Hu N, Shu C, Chen X. Adult attachment and self-disclosure on social networking site: A content analysis of Sina Weibo. Personality and Individual Differences 2019;138:96
    CrossRef
  11. Soron TR. “I will kill myself” – The series of posts in Facebook and unnoticed departure of a life. Asian Journal of Psychiatry 2019;44:55
    CrossRef
  12. Day J, Freiberg K, Hayes A, Homel R. Towards Scalable, Integrative Assessment of Children’s Self-Regulatory Capabilities: New Applications of Digital Technology. Clinical Child and Family Psychology Review 2019;22(1):90
    CrossRef
  13. Pourmand A, Roberson J, Caggiula A, Monsalve N, Rahimi M, Torres-Llenza V. Social Media and Suicide: A Review of Technology-Based Epidemiology and Risk Assessment. Telemedicine and e-Health 2019;25(10):880
    CrossRef
  14. Kim H, Lee S, Lee S, Hong S, Kang H, Kim N. Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone. JMIR mHealth and uHealth 2019;7(10):e14149
    CrossRef
  15. Liang Y, Zheng X, Zeng DD. A survey on big data-driven digital phenotyping of mental health. Information Fusion 2019;52:290
    CrossRef
  16. Liu X, Liu X, Sun J, Yu NX, Sun B, Li Q, Zhu T. Proactive Suicide Prevention Online (PSPO): Machine Identification and Crisis Management for Chinese Social Media Users With Suicidal Thoughts and Behaviors. Journal of Medical Internet Research 2019;21(5):e11705
    CrossRef
  17. Ghani NA, Hamid S, Targio Hashem IA, Ahmed E. Social media big data analytics: A survey. Computers in Human Behavior 2019;101:417
    CrossRef
  18. Pyenson B, Alston M, Gomberg J, Han F, Khandelwal N, Dei M, Son M, Vora J. Applying Machine Learning Techniques to Identify Undiagnosed Patients with Exocrine Pancreatic Insufficiency. Journal of Health Economics and Outcomes Research 2019;6(2):32
    CrossRef
  19. Notredame C, Morgiève M, Morel F, Berrouiguet S, Azé J, Vaiva G. Distress, Suicidality, and Affective Disorders at the Time of Social Networks. Current Psychiatry Reports 2019;21(10)
    CrossRef
  20. Yin Z, Sulieman LM, Malin BA. A systematic literature review of machine learning in online personal health data. Journal of the American Medical Informatics Association 2019;26(6):561
    CrossRef
  21. Aladağ AE, Muderrisoglu S, Akbas NB, Zahmacioglu O, Bingol HO. Detecting Suicidal Ideation on Forums: Proof-of-Concept Study. Journal of Medical Internet Research 2018;20(6):e215
    CrossRef
  22. Cabrera D, Roy D, Chisolm MS. Social Media Scholarship and Alternative Metrics for Academic Promotion and Tenure. Journal of the American College of Radiology 2018;15(1):135
    CrossRef
  23. Wang Z, Yu G, Tian X. Exploring Behavior of People with Suicidal Ideation in a Chinese Online Suicidal Community. International Journal of Environmental Research and Public Health 2018;16(1):54
    CrossRef
  24. O’Connor RC, Portzky G. Looking to the Future: A Synthesis of New Developments and Challenges in Suicide Research and Prevention. Frontiers in Psychology 2018;9
    CrossRef
  25. Jasso-Medrano JL, López-Rosales F. Measuring the relationship between social media use and addictive behavior and depression and suicide ideation among university students. Computers in Human Behavior 2018;87:183
    CrossRef
  26. Ortiz P, Khin Khin E. Traditional and new media's influence on suicidal behavior and contagion. Behavioral Sciences & the Law 2018;36(2):245
    CrossRef
  27. Schlichthorst M, King K, Turnure J, Sukunesan S, Phelps A, Pirkis J. Influencing the Conversation About Masculinity and Suicide: Evaluation of the Man Up Multimedia Campaign Using Twitter Data. JMIR Mental Health 2018;5(1):e14
    CrossRef
  28. Du J, Zhang Y, Luo J, Jia Y, Wei Q, Tao C, Xu H. Extracting psychiatric stressors for suicide from social media using deep learning. BMC Medical Informatics and Decision Making 2018;18(S2)
    CrossRef
  29. Liu LL, Li TM, Teo AR, Kato TA, Wong PW. Harnessing Social Media to Explore Youth Social Withdrawal in Three Major Cities in China: Cross-Sectional Web Survey. JMIR Mental Health 2018;5(2):e34
    CrossRef
  30. Chan M, Li TMH, Law YW, Wong PWC, Chau M, Cheng C, Fu KW, Bacon-Shone J, Cheng QE, Yip PSF, van Amelsvoort T. Engagement of vulnerable youths using internet platforms. PLOS ONE 2017;12(12):e0189023
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.7276)

:
  1. Vizcarra J, Fukuda K, Kozaki K. Semantic Technology. 2020. Chapter 3:35
    CrossRef
  2. Kasperiuniene J, Briediene M, Zydziunaite V. Computer Supported Qualitative Research. 2020. Chapter 7:89
    CrossRef
  3. Gao J, Cheng Q, Yu PLH. Proceedings of the Future Technologies Conference (FTC) 2018. 2019. Chapter 30:385
    CrossRef