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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

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
  3. Habib D, Depala K, Lin J, Le S, McFall N, Dewan S, Huang J, Habib M, Bishay A, Siebor K, Babaoglu G, Chowdhury N, Moberly A. Patient Experiences in the Cochlear Implant Reddit Community: Comparing Human and Large Language Model Categorization. American Journal of Audiology 2026:1 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
  2. James T, Acharya S. 2025 2nd Asian Conference on Intelligent Technologies (ACOIT). A Comprehensive Study on Sentimental Social Media Analysis of Vaccine Discourse View