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

Depression and Mood Disorders; Suicide Prevention (1363) Ethics, Privacy, and Legal Issues (479) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Digital Biomarkers and Digital Phenotyping (191) Diagnostic Tools in Mental Health (242)

Published on in Vol 6, No 11 (2019): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12942, first published .
Public Opinions on Using Social Media Content to Identify Users With Depression and Target Mental Health Care Advertising: Mixed Methods Survey

Public Opinions on Using Social Media Content to Identify Users With Depression and Target Mental Health Care Advertising: Mixed Methods Survey

Public Opinions on Using Social Media Content to Identify Users With Depression and Target Mental Health Care Advertising: Mixed Methods Survey

Authors of this article:

Elizabeth Ford1 Author Orcid Image ;   Keegan Curlewis1 Author Orcid Image ;   Akkapon Wongkoblap2 Author Orcid Image ;   Vasa Curcin3 Author Orcid Image
Article Authors Cited by (31) Tweetations (14) Metrics

Journals

  1. Di Cara N, Boyd A, Tanner A, Al Baghal T, Calderwood L, Sloan L, Davis O, Haworth C. Views on social media and its linkage to longitudinal data from two generations of a UK cohort study. Wellcome Open Research 2020;5:44 View
  2. Hochheiser H, Valdez R. Human-Computer Interaction, Ethics, and Biomedical Informatics. Yearbook of Medical Informatics 2020;29(01):093 View
  3. Zhong Z. Internet Public Opinion Evolution in the COVID-19 Event and Coping Strategies. Disaster Medicine and Public Health Preparedness 2021;15(6):e27 View
  4. Di Cara N, Boyd A, Tanner A, Al Baghal T, Calderwood L, Sloan L, Davis O, Haworth C. Views on social media and its linkage to longitudinal data from two generations of a UK cohort study. Wellcome Open Research 2020;5:44 View
  5. Nicholas J, Onie S, Larsen M. Ethics and Privacy in Social Media Research for Mental Health. Current Psychiatry Reports 2020;22(12) View
  6. Ford E, Shepherd S, Jones K, Hassan L. Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review. Frontiers in Digital Health 2021;2 View
  7. Wang T, Bashir M. Privacy considerations when predicting mental health using social media. Proceedings of the Association for Information Science and Technology 2020;57(1) View
  8. MacDuffie K, Ransom S, Klein E. Neuroethics Inside and Out: A Comparative Survey of Neural Device Industry Representatives and the General Public on Ethical Issues and Principles in Neurotechnology. AJOB Neuroscience 2022;13(1):44 View
  9. Lee E, Torous J, De Choudhury M, Depp C, Graham S, Kim H, Paulus M, Krystal J, Jeste D. Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2021;6(9):856 View
  10. Wongkoblap A, Vadillo M, Curcin V. Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study. JMIR Mental Health 2021;8(8):e19824 View
  11. 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
  12. Shankar S, Tewari V. Understanding the Emotional Intelligence Discourse on Social Media: Insights from the Analysis of Twitter. Journal of Intelligence 2021;9(4):56 View
  13. Houssein E, Mohamed R, Ali A. Machine Learning Techniques for Biomedical Natural Language Processing: A Comprehensive Review. IEEE Access 2021;9:140628 View
  14. Garg M. Mental Health Analysis in Social Media Posts: A Survey. Archives of Computational Methods in Engineering 2023;30(3):1819 View
  15. 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
  16. Harris D, Krishnan A. Exploring the Association Between Suicide Prevention Public Service Announcements and User Comments on YouTube: A Computational Text Analysis Approach. Journal of Health Communication 2023;28(5):302 View
  17. Eaton M, Probst Y, Smith M. Characterizing the Discourse of Popular Diets to Describe Information Dispersal and Identify Leading Voices, Interaction, and Themes of Mental Health: Social Network Analysis. JMIR Infodemiology 2023;3:e38245 View
  18. 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
  19. Wang Y, Chukwusa E, Koffman J, Curcin V. Public Opinions About Palliative and End-of-Life Care During the COVID-19 Pandemic: Twitter-Based Content Analysis. JMIR Formative Research 2023;7:e44774 View
  20. Rozier M, Scroggins S, Loux T, Shacham E. Personal Location as Health-Related Data: Public Knowledge, Public Concern, and Personal Action. Value in Health 2023;26(9):1314 View
  21. He X, Hu J, Yin M, Zhang W, Qiu B. Screen Media Use Affects Subcortical Structures, Resting-State Functional Connectivity, and Mental Health Problems in Early Adolescence. Brain Sciences 2023;13(10):1452 View
  22. Ito-Jaeger S, Lane G, Dowthwaite L, Webb H, Patel M, Rawsthorne M, Portillo V, Jirotka M, Perez Vallejos E. TrustScapes: A Visualisation Tool to Capture Stakeholders’ Concerns and Recommendations About Data Protection, Algorithmic Bias, and Online Safety. International Journal of Qualitative Methods 2023;22 View
  23. Holtorf A, Danyliv A, Krause A, Hanna A, Venable Y, Mattingly T, Huang L, Pierre M, Silveira Silva A, Walsh D. Ethical and legal considerations in social media research for health technology assessment: conclusions from a scoping review. International Journal of Technology Assessment in Health Care 2023;39(1) View
  24. Mao K, Wu Y, Chen J. A systematic review on automated clinical depression diagnosis. npj Mental Health Research 2023;2(1) View
  25. Frost E, Bosward R, Aquino Y, Braunack-Mayer A, Carter S. Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods. International Journal of Medical Informatics 2024;186:105417 View
  26. Walschots Q, Zarchev M, Unkel M, Kamperman A. Using Wearable Technology to Detect, Monitor, and Predict Major Depressive Disorder—A Scoping Review and Introductory Text for Clinical Professionals. Algorithms 2024;17(9):408 View
  27. Owen D, Lynham A, Smart S, Pardiñas A, Camacho Collados J. AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges. Journal of Medical Internet Research 2024;26:e59225 View
  28. Pyle C, Roemmich K, Andalibi N. U.S. Job-Seekers' Organizational Justice Perceptions of Emotion AI-Enabled Interviews. Proceedings of the ACM on Human-Computer Interaction 2024;8(CSCW2):1 View

Books/Policy Documents

  1. Wongkoblap A, Vadillo M, Curcin V. Mental Health in a Digital World. View
  2. Kumar Attar R, Komal . Artificial Intelligence for Innovative Healthcare Informatics. View