QualiGPT: GPT as an easy-to-use tool for qualitative coding
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Abstract (arXiv)
Qualitative research delves deeply into individual complex perspectives on technology and various phenomena. However, a meticulous analysis of qualitative data often requires a significant amount of time, especially during the crucial coding stage. Although there is software specifically designed for qualitative evaluation, many of these platforms fall short in terms of automatic coding, intuitive usability, and cost-effectiveness. With the rise of Large Language Models (LLMs) such as GPT-3 and its successors, we are at the forefront of a transformative era for enhancing qualitative analysis. In this paper, we introduce QualiGPT, a specialized tool designed after considering challenges associated with ChatGPT and qualitative analysis. It harnesses the capabilities of the Generative Pretrained Transformer (GPT) and its API for thematic analysis of qualitative data. By comparing traditional manual coding with QualiGPT's analysis on both simulated and actual datasets, we verify that QualiGPT not only refines the qualitative analysis process but also elevates its transparency, credibility, and accessibility. Notably, compared to existing analytical platforms, QualiGPT stands out with its intuitive design, significantly reducing the learning curve and operational barriers for users.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Oct 2023.
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Citing papers per year: 2024: 2; 2025: 5; 2026: 1.
8 papers.
- 2024GPT for Games: A Scoping Review (2020-2023)cited by 10
- 2025From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactionscited by 4
- 2024Leveraging Large Language Models (LLMs) to Support Collaborative Human-AI Online Risk Data Annotationcited by 2
- 2025Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generationcited by 1
- 2025TALLMesh: a simple application for performing Thematic Analysis with Large Language Modelscited by 1
- 2025Human-AI Narrative Synthesis to Foster Shared Understanding in Civic Decision-Makingcited by 1
- 2025Beyond Tokens in Language Models: Interpreting Activations through Text Genre Chunkscited by 1
- 2026How AI Coders Discuss, Disagree, and Reach Consensus: Challenges and Opportunities for LLM-Based Qualitative Codingcited by 0
- 2026How AI Coders Discuss, Disagree, and Reach Consensus: Challenges and Opportunities for LLM-Based Qualitative Coding10 Sep 2026
- 2025Beyond Tokens in Language Models: Interpreting Activations through Text Genre Chunks20 Nov 2025
- 2025Human-AI Narrative Synthesis to Foster Shared Understanding in Civic Decision-Making23 Sep 2025
- 2025From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactions25 Apr 2025
- 2025TALLMesh: a simple application for performing Thematic Analysis with Large Language Models5 Apr 2025
- 2025Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generation14 Mar 2025
- 2024GPT for Games: A Scoping Review (2020-2023)27 Apr 2024
- 2024Leveraging Large Language Models (LLMs) to Support Collaborative Human-AI Online Risk Data Annotation11 Apr 2024