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

Vaccination Sentiment and Anti-Vaccination Infodemiology (62) JMIR Theme Issue: COVID-19 Special Issue (2461) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Infodemiology and Infoveillance (1369) Infectious Diseases (non-STD/STI) (1592) Outbreak and Pandemic Preparedness and Management (1743) Mass Media/Social Media Communication and Campaigns (466) COVID-19 Vaccination (155) Vaccination and Immunization in the Digital Age (378)

Published on in Vol 1, No 1 (2021): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25636, first published .
Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Authors of this article:

Li Crystal Jiang1 Author Orcid Image ;   Tsz Hang Chu1 Author Orcid Image ;   Mengru Sun2 Author Orcid Image
Article Authors Cited by (14) Tweetations (5) Metrics

Journals

  1. Calac A, Haupt M, Li Z, Mackey T. Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study. JMIR Infodemiology 2022;2(1):e33587 View
  2. Zang S, Zhang X, Xing Y, Chen J, Lin L, Hou Z. Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review. Journal of Medical Internet Research 2023;25:e40057 View
  3. Zhao S, Hu S, Zhou X, Song S, Wang Q, Zheng H, Zhang Y, Hou Z. The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review. JMIR Public Health and Surveillance 2023;9:e40201 View
  4. Sigalo N, St Jean B, Frias-Martinez V. Using Social Media to Predict Food Deserts in the United States: Infodemiology Study of Tweets. JMIR Public Health and Surveillance 2022;8(7):e34285 View
  5. Aljedaani W, Saad E, Rustam F, de la Torre Díez I, Ashraf I. Role of Artificial Intelligence for Analysis of COVID-19 Vaccination-Related Tweets: Opportunities, Challenges, and Future Trends. Mathematics 2022;10(17):3199 View
  6. Cascini F, Pantovic A, Al-Ajlouni Y, Failla G, Puleo V, Melnyk A, Lontano A, Ricciardi W. Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature. eClinicalMedicine 2022;48:101454 View
  7. Macdonald E, Gaines J, Taubenfeld E, Labagnara K, Huang A, Winer A, Teper E, Abraham N, Watts K. Analysis of Twitter Engagement in a Progressively More Competitive Urology Match: A Mixed Methods Study. Urology 2022;167:30 View
  8. Park S, Suh Y. A Comprehensive Analysis of COVID-19 Vaccine Discourse by Vaccine Brand on Twitter in Korea: Topic and Sentiment Analysis. Journal of Medical Internet Research 2023;25:e42623 View
  9. Schmid-Petri H, Bürger M, Schlögl S, Schwind M, Mitrović J, Kühn R. The multilingual Twitter-discourse on vaccination in Germany during the COVID-19 pandemic. Media and Communication 2023;11(1):293 View
  10. Slavik C, Yiannakoulias N, Buttle C, Darlington J. ‘Vaccinfluencers’: a study of influential voices criticizing COVID-19 vaccination efforts and negative vaccine information discourse on Twitter. The Communication Review 2023;26(3):300 View
  11. Bouabdallaoui I, Guerouate F, Sbihi M. Hybrid Text Embedding and Evolutionary Algorithm Approach for Topic Clustering in Online Discussion Forums. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 2024;13:e31448 View
  12. Taubert F, Meyer-Hoeven G, Schmid P, Gerdes P, Betsch C. Conspiracy narratives and vaccine hesitancy: a scoping review of prevalence, impact, and interventions. BMC Public Health 2024;24(1) View