Published on 16.05.16 in Vol 3, No 2 (2016): Apr-Jun
Works citing "Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality"
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)
- Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206CrossRef
- 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
- 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):616CrossRef
- 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):e15901CrossRef
- Roy A, Nikolitch K, McGinn R, Jinah S, Klement W, Kaminsky ZA. A machine learning approach predicts future risk to suicidal ideation from social media data. npj Digital Medicine 2020;3(1)CrossRef
- Glenn JJ, Nobles AL, Barnes LE, Teachman BA. Can Text Messages Identify Suicide Risk in Real Time? A Within-Subjects Pilot Examination of Temporally Sensitive Markers of Suicide Risk. Clinical Psychological Science 2020;:216770262090614CrossRef
- Spates K, Ye X, Johnson A. “I just might kill myself”: Suicide expressions on Twitter. Death Studies 2020;44(3):189CrossRef
- Priya A, Garg S, Tigga NP. Predicting Anxiety, Depression and Stress in Modern Life using Machine Learning Algorithms. Procedia Computer Science 2020;167:1258CrossRef
- Sabus C, Johns B, Schultz N, Gagnon K. Exploration of Content and Reach of Physical Therapy-Related Discussion on Twitter. Physical Therapy 2019;99(8):1048CrossRef
- Oexle N, Niederkrotenthaler T, DeLeo D. Emerging trends in suicide prevention research. Current Opinion in Psychiatry 2019;32(4):336CrossRef
- 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;245:869CrossRef
- 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;245:848CrossRef
- Tadesse MM, Lin H, Xu B, Yang L. Detection of Suicide Ideation in Social Media Forums Using Deep Learning. Algorithms 2019;13(1):7CrossRef
- Brown RC, Bendig E, Fischer T, Goldwich AD, Baumeister H, Plener PL, Harris KM. Can acute suicidality be predicted by Instagram data? Results from qualitative and quantitative language analyses. PLOS ONE 2019;14(9):e0220623CrossRef
- O'Grady C, Melia R, Bogue J, O'Sullivan M, Young K, Duggan J. SafePlan: An mHealth approach for Improving Outcomes in Suicide Prevention (Preprint). Journal of Medical Internet Research 2019;CrossRef
- 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):1CrossRef
- 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):561CrossRef
- 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):e0198835CrossRef
- 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):102CrossRef
- 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):e28CrossRef
- 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):e10136CrossRef
- Chiang C, Kasunic A, Savage S. Crowd Coach. Proceedings of the ACM on Human-Computer Interaction 2018;2(CSCW):1CrossRef
- King CA, Arango A, Ewell Foster C. Emerging trends in adolescent suicide prevention research. Current Opinion in Psychology 2018;22:89CrossRef
- 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;11:53CrossRef
- 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
- 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):483CrossRef
- Barnes M, Hanson C, Giraud-Carrier C. The Case for Computational Health Science. Journal of Healthcare Informatics Research 2018;2(1-2):99CrossRef
- 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):1009CrossRef
- 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):e215CrossRef
- Ortiz P, Khin Khin E. Traditional and new media's influence on suicidal behavior and contagion. Behavioral Sciences & the Law 2018;36(2):245CrossRef
- 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):e228CrossRef
- Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1CrossRef
- 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;2:32CrossRef
- 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):e243CrossRef
- 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):2675CrossRef
- 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):166CrossRef
According to Crossref, the following books are citing this article (DOI 10.2196/mental.4822)
:- Lawrence D, Carrington-Jones P, Kyron MJ. Alternatives to Suicide. 2020. :221CrossRef
- Roza TH, Patusco LM, Zimerman A, Ballester P, Passos IC. Precision Medicine for Investigators, Practitioners and Providers. 2020. :331CrossRef
- Liang C, Abbott D, Hong YA, Madadi M, White A. Social Computing and Social Media. Design, Human Behavior and Analytics. 2019. Chapter 25:345CrossRef
- 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 5:77CrossRef
- Ebert DD, Harrer M, Apolinário-Hagen J, Baumeister H. Frontiers in Psychiatry. 2019. Chapter 29:583CrossRef
- Adrian M, Lyon AR. Technology and Adolescent Mental Health. 2018. Chapter 12:155CrossRef