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Citing this Article

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Published on 16.05.16 in Vol 3, No 2 (2016): Apr-Jun

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

Works citing "Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality"

Scott R. Braithwaite, Christophe Giraud-Carrier, Josh West, Michael D. Barnes, Carl Lee Hanson

JMIR Ment Health 2016 (May 16); 3(2):e21 

According to Crossref, the following articles are citing this article (DOI 10.2196/mental.4822):

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

  1. 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
  2. Niederkrotenthaler T, Till B, Garcia D. Celebrity suicide on Twitter: Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Avicii. Journal of Affective Disorders 2019;245:848
    CrossRef
  3. 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
  4. 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 2019;
    CrossRef
  5. Melia R, Francis K, Duggan J, Bogue J, O'Sullivan M, Chambers D, Young K. Mobile Health Technology Interventions for Suicide Prevention: Protocol for a Systematic Review and Meta-Analysis. JMIR Research Protocols 2018;7(1):e28
    CrossRef
  6. Kornfield R, Sarma PK, Shah DV, McTavish F, Landucci G, Pe-Romashko K, Gustafson DH. Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum. Journal of Medical Internet Research 2018;20(6):e10136
    CrossRef
  7. Walters K, Christakis DA, Wright DR, Alamian A. Are Mechanical Turk worker samples representative of health status and health behaviors in the U.S.?. PLOS ONE 2018;13(6):e0198835
    CrossRef
  8. Coşkun M, Ozturan M. #europehappinessmap: A Framework for Multi-Lingual Sentiment Analysis via Social Media Big Data (A Twitter Case Study). Information 2018;9(5):102
    CrossRef
  9. Spates K, Ye X, Johnson A. “I just might kill myself”: Suicide expressions on Twitter. Death Studies 2018;:1
    CrossRef
  10. King CA, Arango A, Ewell Foster C. Emerging trends in adolescent suicide prevention research. Current Opinion in Psychology 2018;22:89
    CrossRef
  11. 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
  12. Brent D. Commentary: A time to reap and a time to sow: reducing the adolescent suicide rate now and in the future: commentary on Cha et al. (2018). Journal of Child Psychology and Psychiatry 2018;59(4):483
    CrossRef
  13. Barnes M, Hanson C, Giraud-Carrier C. The Case for Computational Health Science. Journal of Healthcare Informatics Research 2018;2(1-2):99
    CrossRef
  14. Grant RN, Kucher D, León AM, Gemmell JF, Raicu DS, Fodeh SJ. Automatic extraction of informal topics from online suicidal ideation. BMC Bioinformatics 2018;19(S8)
    CrossRef
  15. 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
  16. Soucy JN, Hadjistavropoulos HD, Couture CA, Owens VA, Dear BF, Titov N. Content of client emails in internet-delivered cognitive behaviour therapy: A comparison between two trials and relationship to client outcome. Internet Interventions 2018;11:53
    CrossRef
  17. Colditz JB, Chu K, Emery SL, Larkin CR, James AE, Welling J, Primack BA. Toward Real-Time Infoveillance of Twitter Health Messages. American Journal of Public Health 2018;108(8):1009
    CrossRef
  18. Cheng Q, Li TM, Kwok C, Zhu T, Yip PS. Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study. Journal of Medical Internet Research 2017;19(7):e243
    CrossRef
  19. Wongkoblap A, Vadillo MA, Curcin V. Researching Mental Health Disorders in the Era of Social Media: Systematic Review. Journal of Medical Internet Research 2017;19(6):e228
    CrossRef
  20. Burnap P, Colombo G, Amery R, Hodorog A, Scourfield J. Multi-class machine classification of suicide-related communication on Twitter. Online Social Networks and Media 2017;2:32
    CrossRef
  21. Cohan A, Young S, Yates A, Goharian N. Triaging content severity in online mental health forums. Journal of the Association for Information Science and Technology 2017;68(11):2675
    CrossRef
  22. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
    CrossRef
  23. Carreiro S, Chai PR, Carey J, Chapman B, Boyer EW. Integrating Personalized Technology in Toxicology: Sensors, Smart Glass, and Social Media Applications in Toxicology Research. Journal of Medical Toxicology 2017;13(2):166
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mental.4822)

:
  1. Liang C, Abbott D, Hong YA, Madadi M, White A. Social Computing and Social Media. Design, Human Behavior and Analytics. 2019. Chapter 25:345
    CrossRef
  2. Kessler RC, Bernecker SL, Bossarte RM, Luedtke AR, McCarthy JF, Nock MK, Pigeon WR, Petukhova MV, Sadikova E, VanderWeele TJ, Zuromski KL, Zaslavsky AM. Personalized Psychiatry. 2019. Chapter 5:77
    CrossRef
  3. Adrian M, Lyon AR. Technology and Adolescent Mental Health. 2018. Chapter 12:155
    CrossRef