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Citing this Article

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Published on 12.05.15 in Vol 2, No 2 (2015): April-June

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

Works citing "Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model"

Li Guan, Bibo Hao, Qijin Cheng, Paul SF Yip, Tingshao Zhu

JMIR Ment Health 2015 (May 12); 2(2):e17 

According to Crossref, the following articles are citing this article (DOI 10.2196/mental.4227):

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

  1. Cheng Q, Kwok C, Zhu T, Guan L, Yip P. Suicide Communication on Social Media and Its Psychological Mechanisms: An Examination of Chinese Microblog Users. International Journal of Environmental Research and Public Health 2015;12(9):11506
    CrossRef
  2. Fodeh SJ, Boudreaux ED, Wang R, Silva D, Bossarte R, Goulet JL, Brandt C, Altalib HH. Suicide Risk on Twitter. International Journal of Knowledge Discovery in Bioinformatics 2018;8(2):1
    CrossRef
  3. Braithwaite SR, Giraud-Carrier C, West J, Barnes MD, Hanson CL. Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality. JMIR Mental Health 2016;3(2):e21
    CrossRef
  4. 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
  5. 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
  6. Haines-Delmont A, Chahal G, Bruen AJ, Wall A, Khan CT, Sadashiv R, Fearnley D. Testing Suicide Risk Prediction Algorithms Using Phone Measurements With Patients in Acute Mental Health Settings: Feasibility Study. JMIR mHealth and uHealth 2020;8(6):e15901
    CrossRef
  7. 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
  8. Li A, Jiao D, Liu X, Sun J, Zhu T. A Psycholinguistic Analysis of Responses to Live-Stream Suicides on Social Media. International Journal of Environmental Research and Public Health 2019;16(16):2848
    CrossRef
  9. Zu X, Diao X, Meng Z. The impact of social media input intensity on firm performance: Evidence from Sina Weibo. Physica A: Statistical Mechanics and its Applications 2019;536:122556
    CrossRef
  10. Li A, Jiao D, Zhu T. Detecting depression stigma on social media: A linguistic analysis. Journal of Affective Disorders 2018;232:358
    CrossRef
  11. 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
  12. 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
  13. 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
  14. Khasawneh A, Chalil Madathil K, Dixon E, Wiśniewski P, Zinzow H, Roth R. Examining the Self-Harm and Suicide Contagion Effects of the Blue Whale Challenge on YouTube and Twitter: Qualitative Study. JMIR Mental Health 2020;7(6):e15973
    CrossRef
  15. Liu D, Fu Q, Wan C, Liu X, Jiang T, Liao G, Qiu X, Liu R. Suicidal Ideation Cause Extraction From Social Texts. IEEE Access 2020;8:169333
    CrossRef
  16. 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
  17. Chancellor S, Baumer EPS, De Choudhury M. Who is the "Human" in Human-Centered Machine Learning. Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1
    CrossRef
  18. 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
  19. Bernert RA, Hilberg AM, Melia R, Kim JP, Shah NH, Abnousi F. Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations. International Journal of Environmental Research and Public Health 2020;17(16):5929
    CrossRef
  20. Hettige NC, Nguyen TB, Yuan C, Rajakulendran T, Baddour J, Bhagwat N, Bani-Fatemi A, Voineskos AN, Mallar Chakravarty M, De Luca V. Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach. General Hospital Psychiatry 2017;47:20
    CrossRef
  21. Wang X, Chen S, Li T, Li W, Zhou Y, Zheng J, Chen Q, Yan J, Tang B. Depression Risk Prediction for Chinese Microblogs via Deep-Learning Methods: Content Analysis. JMIR Medical Informatics 2020;8(7):e17958
    CrossRef
  22. Taylor J, Pagliari C. Mining social media data: How are research sponsors and researchers addressing the ethical challenges?. Research Ethics 2018;14(2):1
    CrossRef
  23. Chancellor S, De Choudhury M. Methods in predictive techniques for mental health status on social media: a critical review. npj Digital Medicine 2020;3(1)
    CrossRef
  24. 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
  25. Acuña Caicedo RW, Gómez Soriano JM, Melgar Sasieta HA. Assessment of supervised classifiers for the task of detecting messages with suicidal ideation. Heliyon 2020;6(8):e04412
    CrossRef
  26. Bruen AJ, Wall A, Haines-Delmont A, Perkins E. Exploring Suicidal Ideation Using an Innovative Mobile App-Strength Within Me: The Usability and Acceptability of Setting up a Trial Involving Mobile Technology and Mental Health Service Users. JMIR Mental Health 2020;7(9):e18407
    CrossRef
  27. 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
    CrossRef
  28. Jacobucci R, Ammerman BA, Tyler Wilcox K. The use of text‐based responses to improve our understanding and prediction of suicide risk. Suicide and Life-Threatening Behavior 2021;51(1):55
    CrossRef
  29. Rassy J, Bardon C, Dargis L, Côté L, Corthésy-Blondin L, Mörch C, Labelle R. Information and Communication Technology Use in Suicide Prevention: Scoping Review. Journal of Medical Internet Research 2021;23(5):e25288
    CrossRef
  30. Acuña Caicedo RW, Gómez Soriano JM, Melgar Sasieta HA. Bootstrapping semi-supervised annotation method for potential suicidal messages. Internet Interventions 2022;28:100519
    CrossRef
  31. Bonifazi G, Cecchini S, Corradini E, Giuliani L, Ursino D, Virgili L. Extracting time patterns from the lifespans of TikTok challenges to characterize non-dangerous and dangerous ones. Social Network Analysis and Mining 2022;12(1)
    CrossRef
  32. Yang BX, Xia L, Liu L, Nie W, Liu Q, Li XY, Ao MQ, Wang XQ, Xie YD, Liu Z, Huang YJ, Huang Z, Gong X, Luo D. A Suicide Monitoring and Crisis Intervention Strategy Based on Knowledge Graph Technology for “Tree Hole” Microblog Users in China. Frontiers in Psychology 2021;12
    CrossRef
  33. . Detecting Suicide Ideation in the Online Environment: A Survey of Methods and Challenges. IEEE Transactions on Computational Social Systems 2022;9(3):679
    CrossRef
  34. Lao C, Lane J, Suominen H. Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study. JMIR Formative Research 2022;6(8):e35563
    CrossRef
  35. Wang R, Yang BX, Ma Y, Wang P, Yu Q, Zong X, Huang Z, Ma S, Hu L, Hwang K, Liu Z. Medical-Level Suicide Risk Analysis: A Novel Standard and Evaluation Model. IEEE Internet of Things Journal 2021;8(23):16825
    CrossRef
  36. Cao L, Zhang H, Feng L. Building and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media. IEEE Transactions on Multimedia 2022;24:87
    CrossRef
  37. Taghvaei N, Masoumi B, Keyvanpour MR. Analytical framework for mental health feature extraction methods in social networks. Intelligent Decision Technologies 2021;15(3):343
    CrossRef
  38. Safa R, Bayat P, Moghtader L. Automatic detection of depression symptoms in twitter using multimodal analysis. The Journal of Supercomputing 2022;78(4):4709
    CrossRef
  39. Zhao Y, Liu D, Wan C, Liu X, Qiu X, Nie J. Find Supports for the Post about Mental Issues: More Than Semantic Matching. ACM Transactions on Asian and Low-Resource Language Information Processing 2022;21(6):1
    CrossRef
  40. Cao L, Zhang H, Wang X, Feng L. Learning Users Inner Thoughts and Emotion Changes for Social Media Based Suicide Risk Detection. IEEE Transactions on Affective Computing 2023;14(2):1280
    CrossRef
  41. Geng S, He Y, Duan L, Yang C, Wu X, Liang G, Niu B. The Association Between Linguistic Characteristics of Physicians’ Communication and Their Economic Returns: Mixed Method Study. Journal of Medical Internet Research 2024;26:e42850
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mental.4227):

  1. Huang Y, Liu X, Zhu T. Human Centered Computing. 2019. Chapter 17:166
    CrossRef
  2. Su Y, Zheng H, Liu X, Zhu T. Human Centered Computing. 2019. Chapter 26:257
    CrossRef
  3. Zhu S, Wang X, Liu P. Chinese Lexical Semantics. 2021. Chapter 34:408
    CrossRef
  4. Guo LY, Xia L, Huang XY, Fu YX, Li XY, Zhou SC, Zhao C, Yang BX. Health Information Science. 2022. Chapter 17:177
    CrossRef
  5. Wongkoblap A, Vadillo MA, Curcin V. Mental Health in a Digital World. 2022. :109
    CrossRef
  6. Liang Z, Liu D, Wan Q, Liu X, Liao G, Wan C. Social Media Processing. 2024. Chapter 4:48
    CrossRef