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

Infodemiology and Infoveillance (1349) JMIR Theme Issue: COVID-19 Special Issue (2452)

Published on in Vol 23, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24889, first published .
A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis

A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis

A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis

Authors of this article:

Shi Chen1, 2 Author Orcid Image ;   Lina Zhou3 Author Orcid Image ;   Yunya Song4 Author Orcid Image ;   Qian Xu5 Author Orcid Image ;   Ping Wang6 Author Orcid Image ;   Kanlun Wang3 Author Orcid Image ;   Yaorong Ge7 Author Orcid Image ;   Daniel Janies8 Author Orcid Image
Article Authors Cited by (10) Tweetations (8) Metrics

Journals

  1. Chen S, Paul R, Janies D, Murphy K, Feng T, Thill J. Exploring Feasibility of Multivariate Deep Learning Models in Predicting COVID-19 Epidemic. Frontiers in Public Health 2021;9 View
  2. Li L, Zhou J, Zhuang J, Zhang Q. Gender-specific emotional characteristics of crisis communication on social media: Case studies of two public health crises. Information Processing & Management 2023;60(3):103299 View
  3. Gao H, Zhao Q, Ning C, Guo D, Wu J, Li L. Does the COVID-19 Vaccine Still Work That “Most of the Confirmed Cases Had Been Vaccinated”? A Content Analysis of Vaccine Effectiveness Discussion on Sina Weibo during the Outbreak of COVID-19 in Nanjing. International Journal of Environmental Research and Public Health 2021;19(1):241 View
  4. 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
  5. Chai Y, Palacios J, Wang J, Fan Y, Zheng S, Sasahara K. Measuring daily-life fear perception change: A computational study in the context of COVID-19. PLOS ONE 2022;17(12):e0278322 View
  6. Chen S, Yin S, Guo Y, Ge Y, Janies D, Dulin M, Brown C, Robinson P, Zhang D. Content and sentiment surveillance (CSI): A critical component for modeling modern epidemics. Frontiers in Public Health 2023;11 View
  7. Dupuy-Zini A, Audeh B, Gérardin C, Duclos C, Gagneux-Brunon A, Bousquet C. Users’ Reactions to Announced Vaccines Against COVID-19 Before Marketing in France: Analysis of Twitter Posts. Journal of Medical Internet Research 2023;25:e37237 View
  8. Zhang H, Liu S, Li R, Yu J, Ye D, Yuan S, Lin H, Huang C, Tang H. MIBPred: Ensemble Learning-Based Metal Ion-Binding Protein Classifier. ACS Omega 2024 View
  9. Nangi M, Kamaruddin S, Adam A, Lestari S. Social Media as a Virtual Public Sphere in Health Education: A Systematic Review from the Perspective of Habermas' Public Sphere Theory. Jurnal Kesehatan Komunitas Indonesia 2024;4(1):36 View
  10. Kumi S, Snow C, Lomotey R, Deters R. Uncovering Concerns of Citizens Through Machine Learning and Social Network Sentiment Analysis. IEEE Access 2024;12:94885 View