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

JMIR Theme Issue: COVID-19 Special Issue (2452) Outbreak and Pandemic Preparedness and Management (1727) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Infectious Diseases (non-STD/STI) (1575)

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 (17) Tweetations (13) Metrics

Journals

  1. Wang A, Lan J, Wang M, Yu C. The Evolution of Rumors on a Closed Social Networking Platform During COVID-19: Algorithm Development and Content Study. JMIR Medical Informatics 2021;9(11):e30467 View
  2. Fang F, Wang T, Tan S, Chen S, Zhou T, Zhang W, Guo Q, Liu J, Holme P, Lu X. Network Structure and Community Evolution Online: Behavioral and Emotional Changes in Response to COVID-19. Frontiers in Public Health 2022;9 View
  3. Zhang C, Xu S, Li Z, Liu G, Dai D, Dong C. The Evolution and Disparities of Online Attitudes Toward COVID-19 Vaccines: Year-long Longitudinal and Cross-sectional Study. Journal of Medical Internet Research 2022;24(1):e32394 View
  4. Ueda M, Watanabe K, Sueki H. 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. Journal of Medical Internet Research 2023;25:e44965 View
  5. Li X, Wang H, Chen C, Grundy J. An Empirical Study on How Well Do COVID-19 Information Dashboards Service Users’ Information Needs. IEEE Transactions on Services Computing 2022;15(3):1178 View
  6. Hu M, Conway M. Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia. JMIR Infodemiology 2022;2(2):e36941 View
  7. Feizollah A, Anuar N, Mehdi R, Firdaus A, Sulaiman A. Understanding COVID-19 Halal Vaccination Discourse on Facebook and Twitter Using Aspect-Based Sentiment Analysis and Text Emotion Analysis. International Journal of Environmental Research and Public Health 2022;19(10):6269 View
  8. Gómez-Salgado J, Palomino-Baldeón J, Ortega-Moreno M, Fagundo-Rivera J, Allande-Cussó R, Ruiz-Frutos C. COVID-19 information received by the Peruvian population, during the first phase of the pandemic, and its association with developing psychological distress. Medicine 2022;101(5):e28625 View
  9. Alhuzali H, Zhang T, Ananiadou S. Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis. Journal of Medical Internet Research 2022;24(10):e40323 View
  10. Md Suhaimin M, Ahmad Hijazi M, Moung E, Nohuddin P, Chua S, Coenen F. Social media sentiment analysis and opinion mining in public security: Taxonomy, trend analysis, issues and future directions. Journal of King Saud University - Computer and Information Sciences 2023;35(9):101776 View
  11. Fernández-Pichel M, Aragón M, Saborido-Patiño J, Losada D. Personality trait analysis during the COVID-19 pandemic: a comparative study on social media. Journal of Intelligent Information Systems 2024;62(1):117 View
  12. O'Connor K, Golder S, Weissenbacher D, Klein A, Magge A, Gonzalez-Hernandez G. Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping Review. Journal of Medical Internet Research 2024;26:e47923 View
  13. Elkefi S, Tounsi A. Examining public perceptions and concerns about the impact of heatwaves on health outcomes using Twitter data. The Journal of Climate Change and Health 2024;17:100320 View
  14. Afyouni I, Hashim I, Aghbari Z, Elsaka T, Almahmoud M, Abualigah L. Insights from the COVID-19 Pandemic: A Survey of Data Mining and Beyond. Applied Spatial Analysis and Policy 2024;17(3):1359 View

Books/Policy Documents

  1. Ansar S, Arya S, Dwivedi S, Soni N, Yadav A, Pathak P. Computer Vision and Robotics. View