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

JMIR Theme Issue: COVID-19 Special Issue (2238) Infodemiology and Infoveillance (1124) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1399) Machine Learning (1121) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (921) Outbreak and Pandemic Preparedness and Management (1529) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1385)

Published on in Vol 22 , No 11 (2020) :November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20550, first published .
Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach

Authors of this article:

Jia Xue 1, 2 Author Orcid Image ;   Junxiang Chen 3 Author Orcid Image ;   Ran Hu 1 Author Orcid Image ;   Chen Chen 4 Author Orcid Image ;   Chengda Zheng 2 Author Orcid Image ;   Yue Su 5, 6 Author Orcid Image ;   Tingshao Zhu 5 Author Orcid Image
Article Authors Cited by (157) Tweetations (12) Metrics

Journals

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  126. Laureate C, Buntine W, Linger H. A systematic review of the use of topic models for short text social media analysis. Artificial Intelligence Review 2023 View
  127. Clark S, Lomax N. Using e-petition data to quantify public concerns during the COVID-19 pandemic: a case study of England. Policy Studies 2023:1 View

Books/Policy Documents

  1. Ganguly C, Nayak S, Gupta A. Artificial Intelligence, Machine Learning, and Mental Health in Pandemics. View
  2. Tan A, Estuar M, Co N, Tan H, Abao R, Aureus J. Social Computing and Social Media: Design, User Experience and Impact. View
  3. Esparza J, Bejarano G, Ramesh A, Seetharam A. Computational Data and Social Networks. View
  4. Ghosal A, Gupta N, Nandi E, Somolu H. Artificial Intelligence and Machine Learning Methods in COVID-19 and Related Health Diseases. View
  5. Kovalchuk O, Slobodzian V, Sobko O, Molchanova M, Mazurets O, Barmak O, Krak I, Savina N. Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making. View
  6. Mallikarjuna B, D. J. A, M. S, Sabharwal M. Handbook of Research on Advances in Data Analytics and Complex Communication Networks. View
  7. Dhandapani A, Balasubramaniam A, Balasubramaniam T, Paul A. Machine Intelligence and Data Science Applications. View
  8. Utsu K, Yagi N, Fukushima A, Takemori Y, Okazaki A, Uchida O. Information Technology in Disaster Risk Reduction. View
  9. Yuan K, Zhang M. Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. View
  10. Dhir K, Singh P, Dwivedi Y, Sawhney S, Sawhney R. Co-creating for Context in the Transfer and Diffusion of IT. View
  11. Apolinario-Arzube O, García-Díaz J, Roldán D, Prieto-González L, Casal G, Valencia-García R. Technologies and Innovation. View
  12. Dzitac D. Data Science in Applications. View