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

Vaccination Sentiment and Anti-Vaccination Infodemiology (58) JMIR Theme Issue: COVID-19 Special Issue (2450) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1038) Vaccination and Immunization in the Digital Age (374) Infodemiology and Infoveillance (1346) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1637) Outbreak and Pandemic Preparedness and Management (1721)

Published on in Vol 3 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40575, first published .
Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis

Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis

Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis

Authors of this article:

Vlad Honcharov1, 2 Author Orcid Image ;   Jiawei Li3, 4 Author Orcid Image ;   Maribel Sierra1, 2 Author Orcid Image ;   Natalie A Rivadeneira1, 2 Author Orcid Image ;   Kristan Olazo1, 2 Author Orcid Image ;   Thu T Nguyen5, 6 Author Orcid Image ;   Tim K Mackey3, 4, 7 Author Orcid Image ;   Urmimala Sarkar1, 2 Author Orcid Image
Article Authors Cited by (5) Tweetations (5) Metrics

Journals

  1. Mori Y, Miyatake N, Suzuki H, Mori Y, Okada S, Tanimoto K. Comparison of Impressions of COVID-19 Vaccination and Influenza Vaccination in Japan by Analyzing Social Media Using Text Mining. Vaccines 2023;11(8):1327 View
  2. Haupt M, Chiu M, Chang J, Li Z, Cuomo R, Mackey T, Cresci S. Detecting nuance in conspiracy discourse: Advancing methods in infodemiology and communication science with machine learning and qualitative content coding. PLOS ONE 2023;18(12):e0295414 View
  3. Deiner M, Deiner N, Hristidis V, McLeod S, Doan T, Lietman T, Porco T. Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study. Journal of Medical Internet Research 2024;26:e49139 View
  4. Deiner M, Honcharov V, Li J, Mackey T, Porco T, Sarkar U. Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study. JMIR Infodemiology 2024;4:e59641 View
  5. Bin Abdulrahman K, Bin Abdulrahman A. Scrutinizing the COVID-19 vaccine safety debate. Human Vaccines & Immunotherapeutics 2024;20(1) View