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

Data Sources and Open Data for Infodemiology (16) Public Health Informatics (93) JMIR Theme Issue: COVID-19 Special Issue (2461) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1666) Infodemiology and Infoveillance (1369) Development of Instruments and Surveys (86) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Vaccination and Immunization in the Digital Age (378) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (847)

Published on in Vol 3 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43700, first published .
Using COVID-19 Vaccine Attitudes Found in Tweets to Predict Vaccine Perceptions in Traditional Surveys: Infodemiology Study

Using COVID-19 Vaccine Attitudes Found in Tweets to Predict Vaccine Perceptions in Traditional Surveys: Infodemiology Study

Using COVID-19 Vaccine Attitudes Found in Tweets to Predict Vaccine Perceptions in Traditional Surveys: Infodemiology Study

Authors of this article:

Nekabari Sigalo1 Author Orcid Image ;   Vanessa Frias-Martinez1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Nekabari Sigalo   1 , BSc, MPH, PhD ;   Vanessa Frias-Martinez   1 , BSc, MSc, PhD

1 College of Information Studies, University of Maryland, College Park, MD, United States

Corresponding Author:

  • Nekabari Sigalo, BSc, MPH, PhD
  • College of Information Studies
  • University of Maryland
  • 4130 Campus Dr
  • College Park, MD, 20742
  • United States
  • Phone: 1 301 405 2033
  • Email: nsigalo@terpmail.umd.edu