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

Vaccination Sentiment and Anti-Vaccination Infodemiology (33) Infodemiology and Infoveillance (1003) JMIR Theme Issue: COVID-19 Special Issue (2087) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (820)

Published on in Vol 2 , No 1 (2022) :Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33909, first published .
Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter Posts

Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter Posts

Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter Posts

Authors of this article:

Ranganathan Chandrasekaran 1 Author Orcid Image ;   Rashi Desai 1 Author Orcid Image ;   Harsh Shah 1 Author Orcid Image ;   Vivek Kumar 1 Author Orcid Image ;   Evangelos Moustakas 2 Author Orcid Image
Article Authors Cited by (7) Tweetations (4) Metrics

Journals

  1. Ackleh-Tingle J, Jordan N, Onwubiko U, Chandra C, Harton P, Rentmeester S, Chamberlain A. Prevalence and Correlates of COVID-19 Vaccine Information on Family Medicine Practices’ Websites in the United States: Cross-sectional Website Content Analysis. JMIR Formative Research 2022;6(11):e38425 View
  2. Chandrasekaran R, Bapat P, Jeripity Venkata P, Moustakas E. Do Patients Assess Physicians Differently in Video Visits as Compared with In-Person Visits? Insights from Text-Mining Online Physician Reviews. Telemedicine and e-Health 2023 View
  3. 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
  4. Saini V, Liang L, Yang Y, Le H, Wu C. The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model. JMIR Infodemiology 2022;2(1):e37077 View
  5. Lee C, Kong P, Yang W. Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models. Journal of Mathematics 2023;2023:1 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

Books/Policy Documents

  1. Siewert S, Kieslich K, Braun M, Dabrock P. Synthetic Biology and the Question of Public Participation. View