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

Michiko Ueda 1, 2 , PhD ;   Kohei Watanabe 3 , PhD ;   Hajime Sueki 4 , PhD

1 Department of Public Administration and International Affairs , The Maxwell School of Citizenship and Public Affairs , Syracuse University , Syracuse , NY , US

2 Center for Policy Research , The Maxwell School of Citizenship and Public Affairs , Syracuse University , Syracuse , NY , US

3 Waseda Institute for Advanced Study , Waseda University , Tokyo , JP

4 Faculty of Human Sciences , Wako University , Tokyo , JP

Corresponding Author:

  • Michiko Ueda , PhD
  • Department of Public Administration and International Affairs
  • The Maxwell School of Citizenship and Public Affairs
  • Syracuse University
  • 426 Eggers Hall
  • Syracuse , NY
  • US
  • Phone: 1 3154439046
  • Email: miueda@syr.edu