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

Natural Language Processing (886) Advanced Data Analytics in eHealth (201) Information Seeking, Information Needs (553) Infoveillance and Social Listening (304) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1893) Public (e)Health, Digital Epidemiology and Public Health Informatics (968) Vaccination and Immunization in the Digital Age (436)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57164, first published .
Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation

Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation

Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation

Authors of this article:

Liang-Chin Huang1 Author Orcid Image ;   Amanda L Eiden2 Author Orcid Image ;   Long He1 Author Orcid Image ;   Augustine Annan1 Author Orcid Image ;   Siwei Wang1 Author Orcid Image ;   Jingqi Wang1 Author Orcid Image ;   Frank J Manion1 Author Orcid Image ;   Xiaoyan Wang1 Author Orcid Image ;   Jingcheng Du1 Author Orcid Image ;   Lixia Yao2 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Evans S, Schmitt J, Kalra D, Sokol T, Holt D. Policy brief: Improving national vaccination decision-making through data. Frontiers in Public Health 2024;12 View
  2. Annan A, Eiden A, Wang D, Du J, Rastegar-Mojarad M, Nomula V, Wang X. Evaluating Large Language Models for Sentiment Analysis and Hesitancy Analysis on Vaccine Posts From Social Media: Qualitative Study. JMIR Formative Research 2025;9:e64723 View

Conference Proceedings

  1. Soyalp M, Yıldırım G, Keskinöz M. 2025 9th International Symposium on Innovative Approaches in Smart Technologies (ISAS). Strategies for Class Imbalance in Emotion Analysis: A Comparative Evaluation View