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

JMIR Theme Issue: COVID-19 Special Issue (2452) Natural Language Processing (692) Infectious Diseases (non-STD/STI) (1575) Vaccination and Immunization in the Digital Age (374) Machine Learning (1465) Infodemiology and Infoveillance (1349) COVID-19 Vaccination (146) Vaccination Sentiment and Anti-Vaccination Infodemiology (58) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Mass Media/Social Media Communication and Campaigns (461)

Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32685, first published .
Comparing Public Sentiment Toward COVID-19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit

Comparing Public Sentiment Toward COVID-19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit

Comparing Public Sentiment Toward COVID-19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit

Authors of this article:

Cathy Yan1 Author Orcid Image ;   Melanie Law2 Author Orcid Image ;   Stephanie Nguyen3 Author Orcid Image ;   Janelle Cheung4 Author Orcid Image ;   Jude Kong5 Author Orcid Image
Article Authors Cited by (23) Tweetations (9) Metrics

Journals

  1. Bonifazi G, Corradini E, Ursino D, Virgili L. New Approaches to Extract Information From Posts on COVID-19 Published on Reddit. International Journal of Information Technology & Decision Making 2022;21(05):1385 View
  2. Davis J, Huennekens J. YIMBY divided: A qualitative content analysis of YIMBY subreddit data. Journal of Urban Affairs 2024;46(9):1810 View
  3. Yin J. Media Data and Vaccine Hesitancy: Scoping Review. JMIR Infodemiology 2022;2(2):e37300 View
  4. 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
  5. Alhuzali H, Zhang T, Ananiadou S. Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis. Journal of Medical Internet Research 2022;24(10):e40323 View
  6. 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
  7. 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
  8. Zhang C, Xu S, Li Z, Liu G, Dai D, Dong C. The Evolution and Disparities of Online Attitudes Toward COVID-19 Vaccines: Year-long Longitudinal and Cross-sectional Study. Journal of Medical Internet Research 2022;24(1):e32394 View
  9. 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
  10. Ogbuokiri B, Ahmadi A, Bragazzi N, Movahedi Nia Z, Mellado B, Wu J, Orbinski J, Asgary A, Kong J. Public sentiments toward COVID-19 vaccines in South African cities: An analysis of Twitter posts. Frontiers in Public Health 2022;10 View
  11. 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
  12. 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
  13. Amujo O, Ibeke E, Fuzi R, Ogara U, Iwendi C. Sentiment Computation of UK-Originated COVID-19 Vaccine Tweets: A Chronological Analysis and News Effect. Sustainability 2023;15(4):3212 View
  14. Xu Q, Chang V, Jayne C. A systematic review of social media-based sentiment analysis: Emerging trends and challenges. Decision Analytics Journal 2022;3:100073 View
  15. Movahedi Nia Z, Bragazzi N, Asgary A, Orbinski J, Wu J, Kong J. Mpox Panic, Infodemic, and Stigmatization of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis of a Large, Multilingual Social Media Database. Journal of Medical Internet Research 2023;25:e45108 View
  16. 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
  17. 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
  18. Rotolo B, Bin Noon G, Chen H, Butt Z. Public Attitudes Towards Vaccine Passports in Alberta During the “Pandemic of the Unvaccinated”: A Qualitative Analysis of Reddit Posts. International Journal of Public Health 2023;68 View
  19. Hansen R, Baiju N, Gabarron E. Social Media as an Effective Provider of Quality-Assured and Accurate Information to Increase Vaccine Rates: Systematic Review. Journal of Medical Internet Research 2023;25:e50276 View

Books/Policy Documents

  1. Serra G, Portelli B, Scaboro S, Chersoni E. Innovating Health Against Future Pandemics. View