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

Theme Issue: Social Media, Ethics, and COVID-19 Misinformation (35) JMIR Theme Issue: COVID-19 Special Issue (2450) Infodemiology and Infoveillance (1349) Vaccination and Immunization in the Digital Age (374) Infectious Diseases (non-STD/STI) (1567) COVID-19 Vaccination (146) Vaccination Sentiment and Anti-Vaccination Infodemiology (58) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1040) Mass Media/Social Media Communication and Campaigns (461)

Published on in Vol 24, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31726, first published .
COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling

COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling

COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling

Authors of this article:

Luwen Huangfu1, 2 Author Orcid Image ;   Yiwen Mo1 Author Orcid Image ;   Peijie Zhang3 Author Orcid Image ;   Daniel Dajun Zeng3, 4 Author Orcid Image ;   Saike He3, 4 Author Orcid Image
Article Authors Cited by (34) Tweetations (4) Metrics

Journals

  1. Mitera H. Topic-Modeling-Ansätze für Social Media Kommunikation in der Coronapandemie. Information – Wissenschaft & Praxis 2022;73(4):197 View
  2. 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
  3. Abiola O, Abayomi-Alli A, Tale O, Misra S, Abayomi-Alli O. Sentiment analysis of COVID-19 tweets from selected hashtags in Nigeria using VADER and Text Blob analyser. Journal of Electrical Systems and Information Technology 2023;10(1) View
  4. Ogunleye O, Godman B, Fadare J, Mudenda S, Adeoti A, Yinka-Ogunleye A, Ogundele S, Oyawole M, Schönfeldt M, Rashed W, Galal A, Masuka N, Zaranyika T, Kalungia A, Malande O, Kibuule D, Massele A, Chikowe I, Khuluza F, Taruvinga T, Alfadl A, Malik E, Oluka M, Opanga S, Ankrah D, Sefah I, Afriyie D, Tagoe E, Amu A, Msibi M, Etando A, Alabi M, Okwen P, Niba L, Mwita J, Rwegerera G, Kgatlwane J, Jairoun A, Ejekam C, Mavenyengwa R, Murimi-Worstell I, Campbell S, Meyer J. Coronavirus Disease 2019 (COVID-19) Pandemic across Africa: Current Status of Vaccinations and Implications for the Future. Vaccines 2022;10(9):1553 View
  5. Wawrzuta D, Klejdysz J, Jaworski M, Gotlib J, Panczyk M. Attitudes toward COVID-19 Vaccination on Social Media: A Cross-Platform Analysis. Vaccines 2022;10(8):1190 View
  6. 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
  7. Niu Q, Liu J, Kato M, Nagai-Tanima M, Aoyama T. The Effect of Fear of Infection and Sufficient Vaccine Reservation Information on Rapid COVID-19 Vaccination in Japan: Evidence From a Retrospective Twitter Analysis. Journal of Medical Internet Research 2022;24(6):e37466 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. Tokiya M, Hara M, Matsumoto A, Ashenagar M, Nakano T, Hirota Y. Association of Vaccine Confidence and Hesitancy in Three Phases of COVID-19 Vaccine Approval and Introduction in Japan. Vaccines 2022;10(3):423 View
  10. 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
  11. Ljajić A, Prodanović N, Medvecki D, Bašaragin B, Mitrović J. Uncovering the Reasons Behind COVID-19 Vaccine Hesitancy in Serbia: Sentiment-Based Topic Modeling. Journal of Medical Internet Research 2022;24(11):e42261 View
  12. Stracqualursi L, Agati P, Sasahara K. Covid-19 vaccines in Italian public opinion: Identifying key issues using Twitter and Natural Language Processing. PLOS ONE 2022;17(11):e0277394 View
  13. Mondal H, Parvanov E, Singla R, Rayan R, Nawaz F, Ritschl V, Eibensteiner F, Siva Sai C, Cenanovic M, Devkota H, Hribersek M, De R, Klager E, Kletecka-Pulker M, Völkl-Kernstock S, Khalid G, Lordan R, Găman M, Shen B, Stamm T, Willschke H, Atanasov A. Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?. Frontiers in Medicine 2022;9 View
  14. 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
  15. 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
  16. Liang Y, Liu L, Ji Y, Huangfu L, Zeng D. Identifying emotional causes of mental disorders from social media for effective intervention. Information Processing & Management 2023;60(4):103407 View
  17. Liu Y, Shi J, Zhao C, Zhang C. Generalizing factors of COVID-19 vaccine attitudes in different regions: A summary generation and topic modeling approach. DIGITAL HEALTH 2023;9 View
  18. Zaidi Z, Ye M, Samon F, Jama A, Gopalakrishnan B, Gu C, Karunasekera S, Evans J, Kashima Y. Topics in Antivax and Provax Discourse: Yearlong Synoptic Study of COVID-19 Vaccine Tweets. Journal of Medical Internet Research 2023;25:e45069 View
  19. Abboodi B, Pileggi S, Bharathy G. Social Networks in Crisis Management: A Literature Review to Address the Criticality of the Challenge. Encyclopedia 2023;3(3):1157 View
  20. Lossio-Ventura J, Weger R, Lee A, Guinee E, Chung J, Atlas L, Linos E, Pereira F. A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data. JMIR Mental Health 2024;11:e50150 View
  21. Küçük D, Arıcı N. Deep Learning-Based Sentiment and Stance Analysis of Tweets About Vaccination. International Journal on Semantic Web and Information Systems 2023;19(1):1 View
  22. Slavin S, Berman A, Beam A, Navar A, Mittleman M. Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022. Journal of the American Heart Association 2024;13(7) View
  23. Singh P, Lamsal R, Singh M, Shishodia B, Sitaula C, Chand S. GeoCovaxTweets: A global analysis of COVID-19 vaccines and vaccination discourse on social media. Journal of Intelligent & Fuzzy Systems 2024:1 View
  24. Giannouli I, Archontaki I, Karadimitriou A, Papathanassopoulos S. Medical science in peril? analyzing the anti-vaccine rhetoric on greek facebook in the COVID-19 era. Health & New Media Research 2024;8(1):19 View
  25. Chen T, Su L, Ng Y, Wang Y. A longitudinal analysis of usage patterns, topics, and information dissemination related to five names for cultured meat on social media. Current Research in Food Science 2024;9:100859 View
  26. AbuRaed A, Prikryl E, Carenini G, Janjua N. Long COVID Discourse in Canada, the US, and Europe: Analysis Using Topic Modeling and Sentiment Analysis on Twitter Data (Preprint). Journal of Medical Internet Research 2024 View
  27. Xu J, Wu Z, Wass L, Larson H, Lin L. Mapping global public perspectives on mRNA vaccines and therapeutics. npj Vaccines 2024;9(1) View

Books/Policy Documents

  1. Head K, Ridley‐Merriweather K. The Handbook of Language in Public Health and Healthcare. View