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

JMIR Theme Issue: COVID-19 Special Issue (2487) Infodemiology and Infoveillance (1440) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1084) Infectious Diseases (non-STD/STI) (1648) Mass Media/Social Media Communication and Campaigns (501) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1528) Vaccination and Immunization in the Digital Age (396) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1766) Infoveillance and Social Listening (238) COVID-19 Vaccination (162) Vaccination Sentiment and Anti-Vaccination Infodemiology (68)

Published on in Vol 24, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35016, first published .
Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis

Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis

Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis

Authors of this article:

Hyeju Jang1, 2 Author Orcid Image ;   Emily Rempel2 Author Orcid Image ;   Ian Roe2 Author Orcid Image ;   Prince Adu2 Author Orcid Image ;   Giuseppe Carenini1 Author Orcid Image ;   Naveed Zafar Janjua2, 3, 4 Author Orcid Image
Article Authors Cited by (24) Tweetations (55) Metrics

Journals

  1. Hsu J, Tsai R. Increased Online Aggression During COVID-19 Lockdowns: Two-Stage Study of Deep Text Mining and Difference-in-Differences Analysis. Journal of Medical Internet Research 2022;24(8):e38776 View
  2. 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
  3. 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
  4. Piltch-Loeb R, Su M, Bonetti M, Testa M, Stanton E, Toffolutti V, Savoia E. Cross-National Vaccine Concerns and Predictors of Vaccine Hesitancy in Not-Fully Vaccinated Individuals: Findings from USA, Canada, Sweden, and Italy. Vaccines 2022;10(10):1652 View
  5. Canaparo M, Ronchieri E, Scarso L. A natural language processing approach for analyzing COVID-19 vaccination response in multi-language and geo-localized tweets. Healthcare Analytics 2023;3:100172 View
  6. Liu J, Lu S, Zheng H. Analysis of Differences in User Groups and Post Sentiment of COVID-19 Vaccine Hesitators in Chinese Social-Media Platforms. Healthcare 2023;11(9):1207 View
  7. Lindelöf G, Aledavood T, Keller B. Dynamics of the Negative Discourse Toward COVID-19 Vaccines: Topic Modeling Study and an Annotated Data Set of Twitter Posts. Journal of Medical Internet Research 2023;25:e41319 View
  8. Thakur N. Sentiment Analysis and Text Analysis of the Public Discourse on Twitter about COVID-19 and MPox. Big Data and Cognitive Computing 2023;7(2):116 View
  9. Kahraman E, Demirel S, Gündüz U. COVID-19 vaccines in twitter ecosystem: Analyzing perceptions and attitudes by sentiment and text analysis method. Journal of Public Health 2023 View
  10. Zhao Y, Zhang L, Zeng C, Lu W, Chen Y, Fan T. Construction of an aspect-level sentiment analysis model for online medical reviews. Information Processing & Management 2023;60(6):103513 View
  11. Preetha N, Brammya G, Majumder M, Nagarajan M, Therasa M. A systematic review and research contributions on aspect-based sentiment analysis using twitter data. Intelligent Decision Technologies 2023;17(4):1061 View
  12. Nelson V, Bashyal B, Tan P, Argyris Y. Vaccine rhetoric on social media and COVID-19 vaccine uptake rates: A triangulation using self-reported vaccine acceptance. Social Science & Medicine 2024;348:116775 View
  13. P V, V M. Sentiment analysis of multi social media using machine and deep learning models: a review. Multimedia Tools and Applications 2024;83(42):90033 View
  14. Kamiński M, Wieczorek T, Kręgielska-Narożna M, Bogdański P. Tweeting about fatphobia and body shaming: A retrospective infodemiological study. Nutrition 2024;125:112497 View
  15. Ma N, Yu G, Jin X. Investigation of Public Acceptance of Misinformation Correction in Social Media Based on Sentiment Attributions: Infodemiology Study Using Aspect-Based Sentiment Analysis. Journal of Medical Internet Research 2024;26:e50353 View
  16. Kolis J, Brookmeyer K, Chuvileva Y, Voegeli C, Juma S, Ishizumi A, Renfro K, Wilhelm E, Tice H, Fogarty H, Kocer I, Helms J, Verma A. Infodemics and Vaccine Confidence: Protocol for Social Listening and Insight Generation to Inform Action. JMIR Public Health and Surveillance 2024;10:e51909 View
  17. Nath D, Dwivedi S. Aspect-based sentiment analysis: approaches, applications, challenges and trends. Knowledge and Information Systems 2024;66(12):7261 View
  18. Ahmad H, Azhar A, Algosaibi A, Hussain J. Understanding Fluctuations in Public Opinion toward COVID-19 Vaccines: Insights from Social Media Analysis. Sage Open 2024;14(4) View
  19. Weerasinghe S, Oyebode O, Orji R. “No claims, no trials, no compensation. Just roll up your sleeve”: social media communication on vaccine uptake sentiments in Canada. Health & New Media Research 2024;8(2):33 View

Books/Policy Documents

  1. Ogbuokiri B, Ahmadi A, Mellado B, Wu J, Orbinski J, Asgary A, Kong J. Intelligent Systems Design and Applications. View