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

JMIR Theme Issue: COVID-19 Special Issue (2461) Outbreak and Pandemic Preparedness and Management (1743) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Infectious Diseases (non-STD/STI) (1592)

Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26482, first published .
Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study

Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study

Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study

Authors of this article:

Chunyan Zhang1 Author Orcid Image ;   Songhua Xu1 Author Orcid Image ;   Zongfang Li1 Author Orcid Image ;   Shunxu Hu2 Author Orcid Image
Article Authors Cited by (18) Tweetations (13) Metrics

Chunyan Zhang   1 * , MS ;   Songhua Xu   1 * , PhD ;   Zongfang Li   1 * , PhD ;   Shunxu Hu   2 , BS

1 Institute of Medical Artificial Intelligence, The Second Affiliate Hospital of Xi’an Jiaotong University, Xi'an, China

2 School of Mathematics and Statistics, Xi’an Jiaotong University, Xi'an, China

*these authors contributed equally

Corresponding Author:

  • Songhua Xu, PhD
  • Institute of Medical Artificial Intelligence
  • The Second Affiliate Hospital of Xi’an Jiaotong University
  • No.157 Xiwu Road
  • Xi'an
  • China
  • Phone: 86 18710823698
  • Email: songhua_xu1@163.com