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arXiv · 2504.07408

AI Coding with Few-Shot Prompting for Thematic Analysis

Samuel Flanders·Melati Nungsari·Mark Cheong Wing Loong
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Abstract

This paper explores the use of large language models (LLMs), here represented by GPT 3.5-Turbo to perform coding for a thematic analysis. Coding is highly labor intensive, making it infeasible for most researchers to conduct exhaustive thematic analyses of large corpora. We utilize few-shot prompting with higher quality codes generated on semantically similar passages to enhance the quality of the codes while utilizing a cheap, more easily scalable model.

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Samuel Flanders, Melati Nungsari, Mark Cheong Wing Loong. 2025-04-10. AI Coding with Few-Shot Prompting for Thematic Analysis. https://arxiv.org/abs/2504.07408

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