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

Theme Issue 2023: Exploring the Intersection Between Health Information, Misinformation, and Generative AI Technologies (10) Infoveillance and Social Listening (305) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1897) Generative Language Models Including ChatGPT (670)

Published on in Vol 4 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59641, first published .
Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study

Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study

Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study

Authors of this article:

Michael S Deiner1 Author Orcid Image ;   Vlad Honcharov2, 3 Author Orcid Image ;   Jiawei Li4 Author Orcid Image ;   Tim K Mackey4, 5 Author Orcid Image ;   Travis C Porco6 Author Orcid Image ;   Urmimala Sarkar2, 3 Author Orcid Image
Article Authors Cited by (14) Tweetations Metrics

Journals

  1. Li F, Yang Y. Impact of Artificial Intelligence–Generated Content Labels On Perceived Accuracy, Message Credibility, and Sharing Intentions for Misinformation: Web-Based, Randomized, Controlled Experiment. JMIR Formative Research 2024;8:e60024 View
  2. Ferizaj D, Lalk C, Lahmann N, Strube-Lahmann S, Rubel J. Identifying Yalom’s group therapeutic factors in anonymous mental health discussions on Reddit: a mixed-methods analysis using large language models, topic modeling and human supervision. Frontiers in Psychiatry 2025;16 View
  3. Morgan D. Query-Based Analysis: A Strategy for Analyzing Qualitative Data Using ChatGPT. Qualitative Health Research 2025 View
  4. 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
  5. Pelletier J, Watson K, Michel J, McGregor R, Rush S. Effect of a generative artificial intelligence digital scribe on pediatric provider documentation time, cognitive burden, and burnout. JAMIA Open 2025;8(4) View
  6. Yang H, Li M, Zhou H, Xiao Y, Fang Q, Zhou S, Zhang R. Large Language Model Synergy for Ensemble Learning in Medical Question Answering: Design and Evaluation Study. Journal of Medical Internet Research 2025;27:e70080 View
  7. Khosravi M, Izadi R, Aghamaleki Sarvestani M, Bouzarjomehri H, Ahmadi Marzaleh M, Ravangard R. Performance of artificial intelligence large language models (Copilot and Gemini) compared to human experts in healthcare policy making: A mixed-methods cross-sectional study. Health Informatics Journal 2025;31(3) View
  8. Hairston J, Ranjan R, Lakamana S, Spadaro A, Bozkurt S, Perrone J, Sarker A. Automating inductive thematic analyses of health content using large language models: a proof-of-concept study using social media data. JAMIA Open 2025;8(5) View
  9. Mehta S, Paul S, Awiti E, Young S, Zulaika G, Otieno F, Phillips-Howard P, Mason L, Bhaumik R. Evaluation of large language models within GenAI in qualitative research. Scientific Reports 2025;15(1) View
  10. Perez-de-Arriluzea-Madariaga A. Linguistic convergence and divergence of Basque on Twitter: a multilingual computational sociolinguistic analysis. Journal of Multilingual and Multicultural Development 2025:1 View
  11. Álvarez-Martínez F, Esteban L, Frungillo L, Butassi E, Zambon A, Herranz-López M, Aranda M, Pollastro F, Tixier A, Garcia-Perez J, Arráez-Román D, Ross A, Mena P, Edrada-Ebel R, Lyng J, Micol V, Borrás-Rocher F, Barrajón-Catalán E. There are significant differences among artificial intelligence large language models when answering scientific questions. Frontiers in Artificial Intelligence 2025;8 View
  12. Chen J, Tu H, Chang C, Hsu W, Wang P, Liao C, Chen M. Automated Evaluation of Reflection and Feedback Quality in Workplace-Based Assessments by Using Natural Language Processing: Cross-Sectional Competency-Based Medical Education Study. JMIR Medical Education 2025;11:e81718 View
  13. Khalid M, Witmer A. Prompt Engineering for Large Language Model-Assisted Inductive Thematic Analysis. Social Science Computer Review 2025 View

Conference Proceedings

  1. Sharma A, Wallace J. Proceedings of the 7th ACM Conference on Conversational User Interfaces. DeTAILS: Deep Thematic Analysis with Iterative LLM Support View