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Optimizing Generative AI's Accuracy and Transparency in Inductive Thematic Analysis: A Human-AI Comparison

arXiv 2503.16485 ↗First posted 8 Mar 2025cs.HC cs.AIcited by 3

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Abstract (arXiv)

This study highlights the transparency and accuracy of GenAI's inductive thematic analysis, particularly using GPT-4 Turbo API integrated within a stepwise prompt-based Python script. This approach ensured a traceable and systematic coding process, generating codes with supporting statements and page references, which enhanced validation and reproducibility. The results indicate that GenAI performs inductive coding in a manner closely resembling human coders, effectively categorizing themes at a level like the average human coder. However, in interpretation, GenAI extends beyond human coders by situating themes within a broader conceptual context, providing a more generalized and abstract perspective.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 0 of its 16 references that are in the map. First posted on arXiv 8 Mar 2025.

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Citing papers per year: 2025: 1; 2026: 2.

3 papers.