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

JMIR Theme Issue: COVID-19 Special Issue (2554) Outbreak and Pandemic Preparedness and Management (1826) Machine Learning (2076) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Anxiety and Stress Disorders (1330) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions 2023 (409) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1911) Infodemiology and Infoveillance (1558)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44965, first published .
Emotional Distress During COVID-19 by Mental Health Conditions and Economic Vulnerability: Retrospective Analysis of Survey-Linked Twitter Data With a Semisupervised Machine Learning Algorithm

Emotional Distress During COVID-19 by Mental Health Conditions and Economic Vulnerability: Retrospective Analysis of Survey-Linked Twitter Data With a Semisupervised Machine Learning Algorithm

Emotional Distress During COVID-19 by Mental Health Conditions and Economic Vulnerability: Retrospective Analysis of Survey-Linked Twitter Data With a Semisupervised Machine Learning Algorithm

Authors of this article:

Michiko Ueda1, 2 Author Orcid Image ;   Kohei Watanabe3 Author Orcid Image ;   Hajime Sueki4 Author Orcid Image
Article Authors Cited by (9) Tweetations (20) Metrics

Journals

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  2. Baird A, Xia Y. Applying analytics to sociodemographic disparities in mental health. Nature Mental Health 2025;3(1):124 View
  3. DuPont-Reyes M, Zou W, Li J, Villatoro A, Tang L. A machine learning language model approach to evaluating mental health awareness content across Spanish- and English-language social media posts on Twitter. Social Psychiatry and Psychiatric Epidemiology 2025;60(9):2249 View
  4. Dilanka R, Rupasingha R. Sentiment Analysis on Suicidal Tendency Affected by the COVID -19 Pandemic: A Comparison of Different Algorithms using Twitter Data. Coronaviruses 2025;6(2) View
  5. Meneses do Rêgo A, Filho I. The influence of instagram on medical education in the age of artificial intelligence: a formal assessment of its utility in health education. Open Access Journal of Science 2024;7(1):61 View

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  1. Abisado M, Rodriguez R, Manuel R, Pacis M, Bautista M, Fabito B, Magtira M, Malolos J. 2025 8th International Conference on Information and Computer Technologies (ICICT). Public Health in the Digital Era: Insights in the Lens of Bibliometric Analysis of Artificial Intelligence in Social Media for Health Monitoring View
  2. Singla U, Sharma N, Khurshid S. 2025 4th OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 5.0. Real-Time Sentiment Analysis for Monitoring Mental Health from Social Media Posts View
  3. Singla U, Sharma N, Khurshid S. 2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS). Real-Time Sentiment Analysis for Monitoring Mental Health from Social Media Posts View