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.
@article{arxiv.2503.16485,
title = {Optimizing Generative AI's Accuracy and Transparency in Inductive Thematic Analysis: A Human-AI Comparison},
author = {Matthew Nyaaba and Min SungEun and Mary Abiswin Apam and Kwame Owoahene Acheampong and Emmanuel Dwamena},
journal= {arXiv preprint arXiv:2503.16485},
year = {2025}
}