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

Formative Evaluation of Digital Health Interventions (4836) Public (e)Health, Digital Epidemiology and Public Health Informatics (2190) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1374) Vaccination and Immunization in the Digital Age (498) Vaccination Sentiment and Anti-Vaccination Infodemiology (104) Applications of AI (806)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64723, first published .
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Evaluating Large Language Models for Sentiment Analysis and Hesitancy Analysis on Vaccine Posts From Social Media: Qualitative Study

Evaluating Large Language Models for Sentiment Analysis and Hesitancy Analysis on Vaccine Posts From Social Media: Qualitative Study

Authors of this article:

Augustine Annan1 Author Orcid Image ;   Amanda L Eiden2 Author Orcid Image ;   Dong Wang2 Author Orcid Image ;   Jingcheng Du1 Author Orcid Image ;   Majid Rastegar-Mojarad1 Author Orcid Image ;   Varun Kumar Nomula2 Author Orcid Image ;   Xiaoyan Wang1 Author Orcid Image
Article Authors Cited by (5) Tweetations Metrics

Journals

  1. Daraghmi E, Zyadeh N. Sentiment Classification of Amazon Product Reviews Based on Machine and Deep Learning Techniques: A Comparative Study. Future Internet 2026;18(3):138 View
  2. Li X, Dai J, Pang H. AI-powered digital innovations in pharmaceuticals research & development: Current landscape and case examples. Journal of Biopharmaceutical Statistics 2026:1 View
  3. Calin C, Deligianni M, South B, Jadhav A, Rocco M, Furqueron Z, Hauber B, Watt S. Using sentiment analysis to quantify the relative desirability and acceptability of drug-product attributes. JAMIA Open 2026;9(3) View

Conference Proceedings

  1. Liu J, He Y. 2026 International Conference on AI in Education Technology and Applications (AIETA). Evaluation and Optimization of Large Language Models for Cross-Cultural Sentiment Analysis and Text Generation View
  2. Kurashkin S, Malashin I, Martysyuk D, Nelyub V, Masich I, Gantimurov A, Borodulin A, Tynchenko V. Companion Proceedings of the ACM Web Conference 2026. EmoTg: Modeling Social Response to Telegram Posts Using LLM and NLP Features View