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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) JMIR Theme Issue: COVID-19 Special Issue (2452) Mass Media/Social Media Communication and Campaigns (461) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infodemiology and Infoveillance (1349) Infectious Diseases (non-STD/STI) (1575) Outbreak and Pandemic Preparedness and Management (1727) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Vaccination and Immunization in the Digital Age (374) Parent and Caregiver Education and Behavior Change for Vaccination (74) Quality/Credibility of eHealth Information and Trust Issues (531) Vaccination Sentiment and Anti-Vaccination Infodemiology (58) Discourse (38)

Published on in Vol 7, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32814, first published .
Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study

Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study

Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study

Authors of this article:

Jueman Zhang1 Author Orcid Image ;   Yi Wang2 Author Orcid Image ;   Molu Shi3 Author Orcid Image ;   Xiuli Wang4 Author Orcid Image
Article Authors Cited by (20) Tweetations (2) Metrics

Journals

  1. Xie W, Damiano A, Jong C. Emotional appeals and social support in organizational YouTube videos during COVID-19. Telematics and Informatics Reports 2022;8:100028 View
  2. Cano-Marin E, Mora-Cantallops M, Sanchez-Alonso S. The power of big data analytics over fake news: A scientometric review of Twitter as a predictive system in healthcare. Technological Forecasting and Social Change 2023;190:122386 View
  3. ÇILGIN C, GÖKÇEN H, GÖKŞEN Y. Twitter’da COVID-19 aşılarına karşı kamu duyarlılığının çoğunluk oylama sınıflandırıcısı temelli makine öğrenmesi ile duygu analizi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 2022;38(2):1093 View
  4. Assefa N, Abdullahi Y, Hemler E, Lankoande B, Madzorera I, Wang D, Ismail A, Chukwu A, Workneh F, Mapendo F, Millogo O, Abubakari S, Febir L, Lyatuu I, Dianou K, Baernighausen T, Soura A, Asante K, Smith E, Vuai S, Worku A, Killewo J, Mwanyika-Sando M, Berhane Y, Sie A, Tajudeen R, Oduola A, Fawzi W. COVID-19 Preventive Practices, Psychological Distress, and Reported Barriers to Healthcare Access during the Pandemic among Adult Community Members in Sub-Saharan Africa: A Phone Survey. The American Journal of Tropical Medicine and Hygiene 2023;108(1):124 View
  5. 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
  6. Danek S, Büttner M, Krois J, Schwendicke F. How Do Users Respond to Mass Vaccination Centers? A Cross-Sectional Study Using Natural Language Processing on Online Reviews to Explore User Experience and Satisfaction with COVID-19 Vaccination Centers. Vaccines 2023;11(1):144 View
  7. 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
  8. Portelli B, Scaboro S, Tonino R, Chersoni E, Santus E, Serra G. Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets. Journal of Medical Internet Research 2022;24(5):e35115 View
  9. 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
  10. Al-Rawi A, Ackah B, Chun W. The Intersectionality of Twitter Responses to Black Canadian Politicians. Social Media + Society 2023;9(1) View
  11. Kwon S, Park A. Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects. Computers in Human Behavior 2023;144:107734 View
  12. Lee J, Kim Y, Zhu X. Liked and shared tweets during the pandemic: the relationship between intrinsic message features and (mis)information engagement. Behaviour & Information Technology 2024;43(8):1596 View
  13. Biswas M, Shah Z. Extracting factors associated with vaccination from Twitter data and mapping to behavioral models. Human Vaccines & Immunotherapeutics 2023;19(3) View
  14. Wang Y, Wang X, Zhang J, Shi M, Wanta W. Tracking attention about COVID-19 vaccines on twitter and newspapers: A dynamic agenda-setting approach. Telematics and Informatics Reports 2024;13:100122 View
  15. Chandrasekaran R, Konaraddi K, Sharma S, Moustakas E. Text-Mining and Video Analytics of COVID-19 Narratives Shared by Patients on YouTube. Journal of Medical Systems 2024;48(1) View
  16. Blackington C, Cayton F. How to Stay Popular: Threat, Framing, and Conspiracy Theory Longevity. Perspectives on Politics 2024:1 View
  17. Zhang J, Wang Y, Mouton M, Zhang J, Shi M. Public Discourse, User Reactions, and Conspiracy Theories on the X Platform About HIV Vaccines: Data Mining and Content Analysis. Journal of Medical Internet Research 2024;26:e53375 View

Books/Policy Documents

  1. Arunkumar P, Jadhav A. Artificial Intelligence: Theory and Applications. View