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

Vaccination Sentiment and Anti-Vaccination Infodemiology (58) JMIR Theme Issue: COVID-19 Special Issue (2452) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Public (e)Health, Digital Epidemiology and Public Health Informatics (725) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641)

Published on in Vol 3 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43703, first published .
Using COVID-19 Vaccine Attitudes on Twitter to Improve Vaccine Uptake Forecast Models in the United States: Infodemiology Study of Tweets

Using COVID-19 Vaccine Attitudes on Twitter to Improve Vaccine Uptake Forecast Models in the United States: Infodemiology Study of Tweets

Using COVID-19 Vaccine Attitudes on Twitter to Improve Vaccine Uptake Forecast Models in the United States: Infodemiology Study of Tweets

Authors of this article:

Nekabari Sigalo1 Author Orcid Image ;   Naman Awasthi2 Author Orcid Image ;   Saad Mohammad Abrar2 Author Orcid Image ;   Vanessa Frias-Martinez1 Author Orcid Image
Article Authors Cited by (3) Tweetations (6) Metrics

Journals

  1. Sigalo N, Frias-Martinez V. Using COVID-19 Vaccine Attitudes Found in Tweets to Predict Vaccine Perceptions in Traditional Surveys: Infodemiology Study. JMIR Infodemiology 2023;3:e43700 View
  2. 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
  3. Sasse K, Mahabir R, Gkountouna O, Crooks A, Croitoru A, Koh K. Understanding the determinants of vaccine hesitancy in the United States: A comparison of social surveys and social media. PLOS ONE 2024;19(6):e0301488 View