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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1842) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1802) Infodemiology and Infoveillance (1468) Depression and Mood Disorders; Suicide Prevention (1536) Mental Health Surveillance and Epidemiology (77) Natural Language Processing (809) Infectious Diseases (non-STD/STI) (1659) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1532) Artificial Intelligence (1781)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53968, first published .
User Dynamics and Thematic Exploration in r/Depression During the COVID-19 Pandemic: Insights From Overlapping r/SuicideWatch Users

User Dynamics and Thematic Exploration in r/Depression During the COVID-19 Pandemic: Insights From Overlapping r/SuicideWatch Users

User Dynamics and Thematic Exploration in r/Depression During the COVID-19 Pandemic: Insights From Overlapping r/SuicideWatch Users

Authors of this article:

Jianfeng Zhu1 Author Orcid Image ;   Ruoming Jin1 Author Orcid Image ;   Deric R Kenne2 Author Orcid Image ;   NhatHai Phan3 Author Orcid Image ;   Wei-Shinn Ku4 Author Orcid Image
Article Authors Cited by (3) Tweetations (6) Metrics

Journals

  1. Zhu J, Zhang X, Jin R, Jiang H, Kenne D. Probing Public Perceptions of Antidepressants on Social Media: Mixed Methods Study. JMIR Formative Research 2025;9:e62680 View
  2. Alhazzaa L, Curcin V. Profiling Generalized Anxiety Disorder on Social Networks: Content and Behavior Analysis. Journal of Medical Internet Research 2025;27:e53399 View
  3. Maharjan J, Jin R, King J, Zhu J, Kenne D. Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on X (formerly Twitter) during the COVID-19 Pandemic: An NLP Approach (Preprint). JMIR Infodemiology 2024 View