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

Methods and New Tools in Mental Health Research (514) JMIR Theme Issue: COVID-19 Special Issue (2510) Chatbots and Conversational Agents (658) Artificial Intelligence (1831) Generative Language Models Including ChatGPT (553)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50150, first published .
A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data

A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data

A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data

Authors of this article:

Juan Antonio Lossio-Ventura1 Author Orcid Image ;   Rachel Weger2 Author Orcid Image ;   Angela Y Lee3 Author Orcid Image ;   Emily P Guinee1 Author Orcid Image ;   Joyce Chung1 Author Orcid Image ;   Lauren Atlas4 Author Orcid Image ;   Eleni Linos5 Author Orcid Image ;   Francisco Pereira1 Author Orcid Image
Article Authors Cited by (30) Tweetations (6) Metrics

Journals

  1. Lau N, Zhao X, O'Daffer A, Weissman H, Barton K. Pediatric Cancer Communication on Twitter: Natural Language Processing and Qualitative Content Analysis. JMIR Cancer 2024;10:e52061 View
  2. Buldur M, Sezer B. Evaluating the accuracy of Chat Generative Pre-trained Transformer version 4 (ChatGPT-4) responses to United States Food and Drug Administration (FDA) frequently asked questions about dental amalgam. BMC Oral Health 2024;24(1) View
  3. 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
  4. Banerjee S, Dunn P, Conard S, Ali A. Mental Health Applications of Generative AI and Large Language Modeling in the United States. International Journal of Environmental Research and Public Health 2024;21(7):910 View
  5. Kim M, Lu X. Exploring the potential of using ChatGPT for rhetorical move-step analysis: The impact of prompt refinement, few-shot learning, and fine-tuning. Journal of English for Academic Purposes 2024;71:101422 View
  6. Fokides E, Peristeraki E. Comparing ChatGPT's correction and feedback comments with that of educators in the context of primary students' short essays written in English and Greek. Education and Information Technologies 2025;30(2):2577 View
  7. Yu H, Fan L, Li L, Zhou J, Ma Z, Xian L, Hua W, He S, Jin M, Zhang Y, Gandhi A, Ma X. Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis. Journal of Healthcare Informatics Research 2024;8(4):658 View
  8. Bedi S, Liu Y, Orr-Ewing L, Dash D, Koyejo S, Callahan A, Fries J, Wornow M, Swaminathan A, Lehmann L, Hong H, Kashyap M, Chaurasia A, Shah N, Singh K, Tazbaz T, Milstein A, Pfeffer M, Shah N. Testing and Evaluation of Health Care Applications of Large Language Models. JAMA 2025;333(4):319 View
  9. Guo Z, Lai A, Thygesen J, Farrington J, Keen T, Li K. Large Language Models for Mental Health Applications: Systematic Review. JMIR Mental Health 2024;11:e57400 View
  10. Nzobonimpa S, Savard J, Caron I, Lawarée J. Automating public policy: a comparative study of conversational artificial intelligence models and human expertise in crafting briefing notes. AI & SOCIETY 2025;40(5):3627 View
  11. Elmitwalli S, Mehegan J, Gallagher A, Alebshehy R. Enhancing sentiment and intent analysis in public health via fine-tuned Large Language Models on tobacco and e-cigarette-related tweets. Frontiers in Big Data 2024;7 View
  12. Smirnov E. Enhancing qualitative research in psychology with large language models: a methodological exploration and examples of simulations. Qualitative Research in Psychology 2025;22(2):482 View
  13. Sebo P. Use of ChatGPT to Explore Gender and Geographic Disparities in Scientific Peer Review. Journal of Medical Internet Research 2024;26:e57667 View
  14. Wang Z, Huang D, Cui J, Zhang X, Ho S, Cambria E. A review of Chinese sentiment analysis: subjects, methods, and trends. Artificial Intelligence Review 2025;58(3) View
  15. Kumar M, Khan L, Chang H. Evolving techniques in sentiment analysis: a comprehensive review. PeerJ Computer Science 2025;11:e2592 View
  16. Casillano N. Education in the ChatGPT Era: A Sentiment Analysis of Public Discourse on the Role of Language Models in Education. Journal Evaluation in Education (JEE) 2024;5(4):144 View
  17. Kim K, Kim S. Large Language Models’ Accuracy in Emulating Human Experts’ Evaluation of Public Sentiments about Heated Tobacco Products on Social Media: Evaluation Study. Journal of Medical Internet Research 2025;27:e63631 View
  18. Jin Y, Liu J, Li P, Wang B, Yan Y, Zhang H, Ni C, Wang J, Li Y, Bu Y, Wang Y. The Applications of Large Language Models in Mental Health: Scoping Review. Journal of Medical Internet Research 2025;27:e69284 View
  19. Li J, Yang Y, Chen R, Zheng D, Pang P, Lam C, Wong D, Wang Y, Wu J. Identifying healthcare needs with patient experience reviews using ChatGPT. PLOS ONE 2025;20(3):e0313442 View
  20. Yang Y, Li J, Guo J, Cheong-Iao Pang P, Wang Y, Yang X, Im S. Performance Evaluation and Application Potential of Small Large Language Models in Complex Sentiment Analysis Tasks. IEEE Access 2025;13:49007 View
  21. Wang M, Ma R, Shen G, Xue J. How Large Language Models Empower the Analysis of Online Public Engagement for Mega Infrastructure Projects: Cases in Hong Kong. IEEE Transactions on Engineering Management 2025;72:1262 View
  22. Mede N, Villanueva I, Chen K. Communicating Scientific Norms in the Hybrid Media Environment: A Mixed-Method Analysis of Social Media Engagement With Watchdog Science Journalism. Journalism & Mass Communication Quarterly 2025 View
  23. Ojemann W, Xie K, Liu K, Chang E, Roth D, Litt B, Ellis C. Zero-Shot Extraction of Seizure Outcomes from Clinical Notes Using Generative Pretrained Transformers. Journal of Healthcare Informatics Research 2025 View
  24. Shao W. Text sentiment classification optimization based on a fine-tuned BERT and large language model. Journal of Computational Methods in Sciences and Engineering 2025 View
  25. Deiner M, Deiner R, Fathy C, Deiner N, Hristidis V, McLeod S, Bukowski T, Doan T, Seitzman G, Lietman T, Porco T. Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study. Journal of Medical Internet Research 2025;27:e65226 View
  26. Chen H, Alfred M, Cohen E. Efficient Detection of Stigmatizing Language in Electronic Health Records via In-Context Learning: A Comparative Analysis and Validation Study (Preprint). JMIR Medical Informatics 2024 View

Conference Proceedings

  1. Xue K, Zhang X, Mao R, Cambria E. 2024 IEEE International Conference on Data Mining Workshops (ICDMW). Understanding the Hidden State of Language Models from the Perspective of Sentiment Analysis View
  2. Hidayaturrahman , Prawira I. 2024 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS). Leveraging Zero-Shot Learning in Large Language Models for Sentiment Analysis: A Comparative Study on the Indonesian Language View
  3. Kaushik P, Sharma P. 2024 International Conference on Advances in Computing, Communication and Materials (ICACCM). Enhancing Mental Health Detection via Machine Learning: A Sentiment Analysis Technique Utilizing Social Media Data View
  4. Khanna D, Aldaeej A. 2025 IEEE/ACM International Workshop on Software-Intensive Business (IWSiB). Analysing sentiments generated through emotions in hybrid work (agile retrospective) meetings View