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

Artificial Intelligence (2159) Natural Language Processing (923) Development and Evaluation of Research Methods, Instruments and Tools (756) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1924) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1142) Smoking Cessation (633) Machine Learning (2091) Generative Language Models Including ChatGPT (722)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63631, first published .
Large Language Models’ Accuracy in Emulating Human Experts’ Evaluation of Public Sentiments about Heated Tobacco Products on Social Media: Evaluation Study

Large Language Models’ Accuracy in Emulating Human Experts’ Evaluation of Public Sentiments about Heated Tobacco Products on Social Media: Evaluation Study

Large Language Models’ Accuracy in Emulating Human Experts’ Evaluation of Public Sentiments about Heated Tobacco Products on Social Media: Evaluation Study

Authors of this article:

Kwanho Kim1 Author Orcid Image ;   Soojong Kim2 Author Orcid Image
Article Authors Cited by (4) Tweetations (1) Metrics

Journals

  1. Olawade D, Aienobe-Asekharen C. Artificial intelligence in tobacco control: A systematic scoping review of applications, challenges, and ethical implications. International Journal of Medical Informatics 2025;202:105987 View
  2. Kim S, Kim K, Kim H. Large language models’ varying accuracy in recognizing risk-promoting and health-supporting sentiments in public health discourse: The cases of HPV vaccination and heated tobacco products. Social Science & Medicine 2025;383:118328 View
  3. Başaranoğlu M, Akbay E, Erdem E. From digital assistants to clinical partners: revolutionizing pediatric urology through large language model-powered decision support and patient education. World Journal of Urology 2025;43(1) View
  4. Areia C, Taylor M, Garcia M, Hernandez J. Sentiment analysis of research attention: the Altmetric proof of concept. Frontiers in Research Metrics and Analytics 2025;10 View