Published on in Vol 19, No 8 (2017): August

A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals

A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals

A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals

Journals

  1. Birnbaum M, Ernala S, Rizvi A, Arenare E, R. Van Meter A, De Choudhury M, Kane J. Detecting relapse in youth with psychotic disorders utilizing patient-generated and patient-contributed digital data from Facebook. npj Schizophrenia 2019;5(1) View
  2. Fernández-Sotos P, Fernández-Caballero A, González P, Aparicio A, Martínez-Gras I, Torio I, Dompablo M, García-Fernández L, Santos J, Rodriguez-Jimenez R. Digital Technology for Internet Access by Patients With Early-Stage Schizophrenia in Spain: Multicenter Research Study. Journal of Medical Internet Research 2019;21(4):e11824 View
  3. Cacheda F, Fernandez D, Novoa F, Carneiro V. Early Detection of Depression: Social Network Analysis and Random Forest Techniques. Journal of Medical Internet Research 2019;21(6):e12554 View
  4. Su Y, Borah P. Who is the agenda setter? Examining the intermedia agenda-setting effect between Twitter and newspapers. Journal of Information Technology & Politics 2019;16(3):236 View
  5. Boyd R, Cai Z. Mental profile mapping: A psychological single-candidate authorship attribution method. PLOS ONE 2018;13(7):e0200588 View
  6. Saha K, Torous J, Ernala S, Rizuto C, Stafford A, De Choudhury M. A computational study of mental health awareness campaigns on social media. Translational Behavioral Medicine 2019;9(6):1197 View
  7. Kim S, Marsch L, Hancock J, Das A. Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data. Journal of Medical Internet Research 2017;19(10):e353 View
  8. Nitzburg G, Weber I, Yom-Tov E. Internet Searches for Medical Symptoms Before Seeking Information on 12-Step Addiction Treatment Programs: A Web-Search Log Analysis. Journal of Medical Internet Research 2019;21(5):e10946 View
  9. Sumner S, Galik S, Mathieu J, Ward M, Kiley T, Bartholow B, Dingwall A, Mork P. Temporal and Geographic Patterns of Social Media Posts About an Emerging Suicide Game. Journal of Adolescent Health 2019;65(1):94 View
  10. Lyons M, Aksayli N, Brewer G. Mental distress and language use: Linguistic analysis of discussion forum posts. Computers in Human Behavior 2018;87:207 View
  11. Guntuku S, Schwartz H, Kashyap A, Gaulton J, Stokes D, Asch D, Ungar L, Merchant R. Variability in Language used on Social Media prior to Hospital Visits. Scientific Reports 2020;10(1) View
  12. Pereira-Sanchez V, Alvarez-Mon M, Asunsolo del Barco A, Alvarez-Mon M, Teo A. Exploring the Extent of the Hikikomori Phenomenon on Twitter: Mixed Methods Study of Western Language Tweets. Journal of Medical Internet Research 2019;21(5):e14167 View
  13. O’Donoghue B, O’Connor K, Thompson A, McGorry P. The need for early intervention for psychosis to persist throughout the COVID-19 pandemic and beyond. Irish Journal of Psychological Medicine 2021;38(3):214 View
  14. Chen Z, Yan T, Wang E, Jiang H, Tang Y, Yu X, Zhang J, Liu C. Detecting Abnormal Brain Regions in Schizophrenia Using Structural MRI via Machine Learning. Computational Intelligence and Neuroscience 2020;2020:1 View
  15. Nugent N, Pendse S, Schatten H, Armey M. Innovations in Technology and Mechanisms of Change in Behavioral Interventions. Behavior Modification 2023;47(6):1292 View
  16. Yoo D, Birnbaum M, Van Meter A, Ali A, Arenare E, Abowd G, De Choudhury M. Designing a Clinician-Facing Tool for Using Insights From Patients’ Social Media Activity: Iterative Co-Design Approach. JMIR Mental Health 2020;7(8):e16969 View
  17. Su Y, Hu J. A territorial dispute or an agenda war? A cross-national investigation of the network agenda-setting (NAS) model. Journal of Information Technology & Politics 2020;17(4):357 View
  18. 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) View
  19. Hswen Y, Naslund J, Brownstein J, Hawkins J. Monitoring Online Discussions About Suicide Among Twitter Users With Schizophrenia: Exploratory Study. JMIR Mental Health 2018;5(4):e11483 View
  20. Yin Z, Sulieman L, Malin B. A systematic literature review of machine learning in online personal health data. Journal of the American Medical Informatics Association 2019;26(6):561 View
  21. Boyd R, Pasca P, Lanning K, Rauthmann J. The Personality Panorama: Conceptualizing Personality Through Big Behavioural Data. European Journal of Personality 2020 View
  22. Gruzd A, Kumar P, Abul-Fottouh D, Haythornthwaite C. Coding and Classifying Knowledge Exchange on Social Media: a Comparative Analysis of the #Twitterstorians and AskHistorians Communities. Computer Supported Cooperative Work (CSCW) 2020;29(6):629 View
  23. Leis A, Ronzano F, Mayer M, Furlong L, Sanz F. Detecting Signs of Depression in Tweets in Spanish: Behavioral and Linguistic Analysis. Journal of Medical Internet Research 2019;21(6):e14199 View
  24. Naslund J, Bondre A, Torous J, Aschbrenner K. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. Journal of Technology in Behavioral Science 2020;5(3):245 View
  25. Baumer E, Guha S, Skeba P, Gay G. All Users are (Not) Created Equal. Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1 View
  26. Birnbaum M, Kulkarni P, Van Meter A, Chen V, Rizvi A, Arenare E, De Choudhury M, Kane J. Utilizing Machine Learning on Internet Search Activity to Support the Diagnostic Process and Relapse Detection in Young Individuals With Early Psychosis: Feasibility Study. JMIR Mental Health 2020;7(9):e19348 View
  27. Hswen Y, Naslund J, Brownstein J, Hawkins J. Online Communication about Depression and Anxiety among Twitter Users with Schizophrenia: Preliminary Findings to Inform a Digital Phenotype Using Social Media. Psychiatric Quarterly 2018;89(3):569 View
  28. Yadav S, Ramteke P, Ekbal A, Saha S, Bhattacharyya P. Exploring Disorder-Aware Attention for Clinical Event Extraction. ACM Transactions on Multimedia Computing, Communications, and Applications 2020;16(1s):1 View
  29. Aguilera J, Farías D, Ortega-Mendoza R, Montes-y-Gómez M. Depression and anorexia detection in social media as a one-class classification problem. Applied Intelligence 2021;51(8):6088 View
  30. Merz A, Gutiérrez-Sacristán A, Bartz D, Williams N, Ojo A, Schaefer K, Huang M, Li C, Sandoval R, Ye S, Cathcart A, Starosta A, Avillach P. Population attitudes toward contraceptive methods over time on a social media platform. American Journal of Obstetrics and Gynecology 2021;224(6):597.e1 View
  31. Dollmat K, Abdullah N. Machine learning in emotional intelligence studies: a survey. Behaviour & Information Technology 2022;41(7):1485 View
  32. Hitczenko K, Mittal V, Goldrick M. Understanding Language Abnormalities and Associated Clinical Markers in Psychosis: The Promise of Computational Methods. Schizophrenia Bulletin 2021;47(2):344 View
  33. Mirlohi Falavarjani S, Jovanovic J, Fani H, Ghorbani A, Noorian Z, Bagheri E. On the causal relation between real world activities and emotional expressions of social media users. Journal of the Association for Information Science and Technology 2021;72(6):723 View
  34. Pavlova A, Berkers P. “Mental Health” as Defined by Twitter: Frames, Emotions, Stigma. Health Communication 2022;37(5):637 View
  35. Birnbaum M, Norel R, Van Meter A, Ali A, Arenare E, Eyigoz E, Agurto C, Germano N, Kane J, Cecchi G. Identifying signals associated with psychiatric illness utilizing language and images posted to Facebook. npj Schizophrenia 2020;6(1) View
  36. Fekih-Romdhane F, Sassi H, Cheour M. The relationship between social media addiction and psychotic-like experiences in a large nonclinical student sample. Psychosis 2021;13(4):349 View
  37. López-Úbeda P, Plaza-del-Arco F, Díaz-Galiano M, Martín-Valdivia M. How Successful Is Transfer Learning for Detecting Anorexia on Social Media?. Applied Sciences 2021;11(4):1838 View
  38. S S, S. Raj J. Analysis of Deep Learning Techniques for Early Detection of Depression on Social Media Network - A Comparative Study. Journal of Trends in Computer Science and Smart Technology 2021;3(1):24 View
  39. Zingg A, Singh T, Myneni S. Analysis of Online Peripartum Depression Communities: Application of Multilabel Text Classification Techniques to Inform Digitally-Mediated Prevention and Management. Frontiers in Digital Health 2021;3 View
  40. Mayor E, Bietti L. Twitter, time and emotions. Royal Society Open Science 2021;8(5):201900 View
  41. Lai J, Ang C, Acharya U, Cheong K. Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification. International Journal of Environmental Research and Public Health 2021;18(11):6099 View
  42. Gooding P, Kariotis T. Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review. JMIR Mental Health 2021;8(6):e24668 View
  43. Yang Y, Al-Garadi M, Love J, Perrone J, Sarker A. Automatic gender detection in Twitter profiles for health-related cohort studies. JAMIA Open 2021;4(2) View
  44. Ricard B, Hassanpour S. Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes. Journal of Medical Internet Research 2021;23(9):e27314 View
  45. Hänsel K, Lin I, Sobolev M, Muscat W, Yum-Chan S, De Choudhury M, Kane J, Birnbaum M. Utilizing Instagram Data to Identify Usage Patterns Associated With Schizophrenia Spectrum Disorders. Frontiers in Psychiatry 2021;12 View
  46. Ziv I, Baram H, Bar K, Zilberstein V, Itzikowitz S, Harel E, Dershowitz N. Morphological characteristics of spoken language in schizophrenia patients – an exploratory study. Scandinavian Journal of Psychology 2022;63(2):91 View
  47. Kelley S, Mhaonaigh C, Burke L, Whelan R, Gillan C. Machine learning of language use on Twitter reveals weak and non-specific predictions. npj Digital Medicine 2022;5(1) View
  48. Fonseka L, Woo B. Social media and schizophrenia: An update on clinical applications. World Journal of Psychiatry 2022;12(7):897 View
  49. Bae Y, Shim M, Lee W. Schizophrenia Detection Using Machine Learning Approach from Social Media Content. Sensors 2021;21(17):5924 View
  50. Góngora Alonso S, Marques G, Agarwal D, De la Torre Díez I, Franco-Martín M. Comparison of Machine Learning Algorithms in the Prediction of Hospitalized Patients with Schizophrenia. Sensors 2022;22(7):2517 View
  51. Feldman J, Hamlyn A, Rice T. Social media in screening and monitoring for early intervention in psychosis. Schizophrenia Research 2021;238:70 View
  52. Roemmich K, Andalibi N. Data Subjects' Conceptualizations of and Attitudes Toward Automatic Emotion Recognition-Enabled Wellbeing Interventions on Social Media. Proceedings of the ACM on Human-Computer Interaction 2021;5(CSCW2):1 View
  53. Li N, Zhang H, Feng L. Incorporating Forthcoming Events and Personality Traits in Social Media Based Stress Prediction. IEEE Transactions on Affective Computing 2023;14(1):603 View
  54. Hacohen-Kerner Y, Manor N, Goldmeier M, Bachar E. Detection of Anorexic Girls-In Blog Posts Written in Hebrew Using a Combined Heuristic AI and NLP Method. IEEE Access 2022;10:34800 View
  55. Price G, Heinz M, Nemesure M, McFadden J, Jacobson N. Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychoses. Frontiers in Psychiatry 2022;13 View
  56. Milton A, Pera M. Into the Unknown: Exploration of Search Engines’ Responses to Users with Depression and Anxiety. ACM Transactions on the Web 2023;17(4):1 View
  57. Franco O, Calkins M, Giorgi S, Ungar L, Gur R, Kohler C, Tang S. Feasibility of Mobile Health and Social Media–Based Interventions for Young Adults With Early Psychosis and Clinical Risk for Psychosis: Survey Study. JMIR Formative Research 2022;6(7):e30230 View
  58. Schick A, Rauschenberg C, Ader L, Daemen M, Wieland L, Paetzold I, Postma M, Schulte-Strathaus J, Reininghaus U. Novel digital methods for gathering intensive time series data in mental health research: scoping review of a rapidly evolving field. Psychological Medicine 2023;53(1):55 View
  59. Trinh Ha P, D’Silva R, Chen E, Koyutürk M, Karakurt G. Identification of intimate partner violence from free text descriptions in social media. Journal of Computational Social Science 2022;5(2):1207 View
  60. FOWLER J, MADAN A, BRUCE C, FRUEH B, KASH B, JONES S, SASANGOHAR F. Improving Psychiatric Care Through Integrated Digital Technologies. Journal of Psychiatric Practice 2021;27(2):92 View
  61. Iyortsuun N, Kim S, Jhon M, Yang H, Pant S. A Review of Machine Learning and Deep Learning Approaches on Mental Health Diagnosis. Healthcare 2023;11(3):285 View
  62. Saha K, Yousuf A, Boyd R, Pennebaker J, De Choudhury M. Social Media Discussions Predict Mental Health Consultations on College Campuses. Scientific Reports 2022;12(1) View
  63. Lejeune A, Robaglia B, Walter M, Berrouiguet S, Lemey C. Use of Social Media Data to Diagnose and Monitor Psychotic Disorders: Systematic Review. Journal of Medical Internet Research 2022;24(9):e36986 View
  64. Yang Y, Xie A, Kim S, Hair J, Al-Garadi M, Sarker A. Automatic Detection of Twitter Users Who Express Chronic Stress Experiences via Supervised Machine Learning and Natural Language Processing. CIN: Computers, Informatics, Nursing 2023;41(9):717 View
  65. Lin Y, Tai L, Chen A. The detection of mental health conditions by incorporating external knowledge. Journal of Intelligent Information Systems 2023;61(2):497 View
  66. Nguyen V, Lu N, Kane J, Birnbaum M, De Choudhury M. Cross-Platform Detection of Psychiatric Hospitalization via Social Media Data: Comparison Study. JMIR Mental Health 2022;9(12):e39747 View
  67. Dhelim S, Chen L, Das S, Ning H, Nugent C, Leavey G, Pesch D, Bantry-White E, Burns D. Detecting Mental Distresses Using Social Behavior Analysis in the Context of COVID-19: A Survey. ACM Computing Surveys 2023;55(14s):1 View
  68. Lundin N, Cowan H, Singh D, Moe A. Lower cohesion and altered first-person pronoun usage in the spoken life narratives of individuals with schizophrenia. Schizophrenia Research 2023;259:140 View
  69. Di Cara N, Maggio V, Davis O, Haworth C. Methodologies for Monitoring Mental Health on Twitter: Systematic Review. Journal of Medical Internet Research 2023;25:e42734 View
  70. Dalrymple-Fraser C. Whose Mental Data? Privacy Inequities and Extended Minds. AJOB Neuroscience 2023;14(2):104 View
  71. Chancellor S, Feuston J, Chang J. Contextual Gaps in Machine Learning for Mental Illness Prediction: The Case of Diagnostic Disclosures. Proceedings of the ACM on Human-Computer Interaction 2023;7(CSCW2):1 View
  72. Ahmad Wani M, ELAffendi M, Shakil K, Shariq Imran A, Abd El-Latif A. Depression Screening in Humans With AI and Deep Learning Techniques. IEEE Transactions on Computational Social Systems 2023;10(4):2074 View
  73. Gashkarimov V, Sultanova R, Efremov I, Asadullin A. Machine learning techniques in diagnostics and prediction of the clinical features of schizophrenia: a narrative review. Consortium Psychiatricum 2023;4(3):43 View
  74. De Choudhury M, Kiciman E. Integrating Artificial and Human Intelligence in Complex, Sensitive Problem Domains: Experiences from Mental Health. AI Magazine 2018;39(3):69 View
  75. Thaxton C, Dardik A. Computer Science meets Vascular Surgery: Keeping a pulse on artificial intelligence. Seminars in Vascular Surgery 2023;36(3):419 View
  76. Birnbaum M, Rizvi A, Faber K, Addington J, Correll C, Gerber C, Lahti A, Loewy R, Mathalon D, Nelson L, Voineskos A, Walker E, Ward E, Kane J. Digital Trajectories to Care in First-Episode Psychosis. Psychiatric Services 2018;69(12):1259 View
  77. Rani S, Ahmed K, Subramani S. From Posts to Knowledge: Annotating a Pandemic-Era Reddit Dataset to Navigate Mental Health Narratives. Applied Sciences 2024;14(4):1547 View
  78. Xu X, Yao B, Dong Y, Gabriel S, Yu H, Hendler J, Ghassemi M, Dey A, Wang D. Mental-LLM. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2024;8(1):1 View
  79. Beer C, Maniora J, Pott C. The Risk of Silence—How the Capital Market Penalizes Social Media Passivity. Journal of Information Systems 2024;38(1):5 View
  80. Li I, Estafanous A, De Choudhury M, Alvarez-Jimenez M, Birnbaum M. Social Media and Early Psychosis Intervention: A Comprehensive Review of the Literature. Current Treatment Options in Psychiatry 2024;11(2):52 View
  81. Suárez-Llevat C, Jiménez-Gómez B, Ruiz-Núñez C, Fernández-Quijano I, Rodriguez-González E, de la Torre-Domingo C, Herrera-Peco I. Social networks use in the context of Schizophrenia: a review of the literature. Frontiers in Psychiatry 2024;15 View
  82. Jaiswal A, Shah A, Harjadi C, Windgassen E, Washington P. Ethics of the Use of Social Media as Training Data for Artificial Intelligence Models used for Digital Phenotyping: Commentary (Preprint). JMIR Formative Research 2024 View
  83. Plank L, Zlomuzica A. Reduced speech coherence in psychosis-related social media forum posts. Schizophrenia 2024;10(1) View

Books/Policy Documents

  1. Dutta S, De Choudhury M. HCI International 2020 – Late Breaking Papers: Interaction, Knowledge and Social Media. View
  2. Rosenfeld A, Benrimoh D, Armstrong C, Mirchi N, Langlois-Therrien T, Rollins C, Tanguay-Sela M, Mehltretter J, Fratila R, Israel S, Snook E, Perlman K, Kleinerman A, Saab B, Thoburn M, Gabbay C, Yaniv-Rosenfeld A. Applications of Big Data in Healthcare. View
  3. Hemtanon S, Aekwarangkoon S, Kittiphattanabawon N. Recent Advances in Information and Communication Technology 2021. View
  4. Schneider H. Artificial Intelligence in Medicine. View
  5. Heinz M, Thomas N, Nguyen N, Griffin T, Jacobson N. Comprehensive Clinical Psychology. View
  6. Schneider H. Artificial Intelligence in Medicine. View