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

JMIR Theme Issue: COVID-19 Special Issue (2490) Infectious Diseases (non-STD/STI) (1653) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1771) Pulmonology, COPD (161) Longitudinal and Cohort Studies in Public Health (345) Machine Learning (1694) Data Science (300) Patient Generated Health Data (8) Data Sources and Open Data for Infodemiology (19) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (404)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54543, first published .
Exploring Psychological Trends in Populations With Chronic Obstructive Pulmonary Disease During COVID-19 and Beyond: Large-Scale Longitudinal Twitter Mining Study

Exploring Psychological Trends in Populations With Chronic Obstructive Pulmonary Disease During COVID-19 and Beyond: Large-Scale Longitudinal Twitter Mining Study

Exploring Psychological Trends in Populations With Chronic Obstructive Pulmonary Disease During COVID-19 and Beyond: Large-Scale Longitudinal Twitter Mining Study

Authors of this article:

Chunyan Zhang1, 2 Author Orcid Image ;   Ting Wang3 Author Orcid Image ;   Caixia Dong2 Author Orcid Image ;   Duwei Dai2 Author Orcid Image ;   Linyun Zhou2 Author Orcid Image ;   Zongfang Li2 Author Orcid Image ;   Songhua Xu2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Chunyan Zhang   1, 2 * , MS ;   Ting Wang   3 * , PhD ;   Caixia Dong   2 , MS ;   Duwei Dai   2 , MS ;   Linyun Zhou   2 , MPH ;   Zongfang Li   2 , PhD ;   Songhua Xu   2 , PhD

1 The High School Affiliated to Xi'an Jiaotong University, Xi'an, China

2 Institute of Medical Artificial Intelligence, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

3 School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China

*these authors contributed equally

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