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Using ChatGPT for Thematic Analysis

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arxiv 2405.08828 v1 pith:HU6FF6J4 submitted 2024-05-13 cs.HC

Aleksei Turobov , Diane Coyle , Verity Harding This is my paper · ORCID
classification cs.HC
keywords researchanalysisthematicchatgptpotentialriskstoolsacademic
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The utilisation of AI-driven tools, notably ChatGPT, within academic research is increasingly debated from several perspectives including ease of implementation, and potential enhancements in research efficiency, as against ethical concerns and risks such as biases and unexplained AI operations. This paper explores the use of the GPT model for initial coding in qualitative thematic analysis using a sample of UN policy documents. The primary aim of this study is to contribute to the methodological discussion regarding the integration of AI tools, offering a practical guide to validation for using GPT as a collaborative research assistant. The paper outlines the advantages and limitations of this methodology and suggests strategies to mitigate risks. Emphasising the importance of transparency and reliability in employing GPT within research methodologies, this paper argues for a balanced use of AI in supported thematic analysis, highlighting its potential to elevate research efficacy and outcomes.

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Cited by 3 Pith papers

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  2. Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study

    cs.HC 2025-05 conditional novelty 5.0 of 10

    GPT-4o with RISEN prompts can perform thematic analysis faster and cheaper, but humans still excel at child-code development, excerpt coding, and theme synthesis.

  3. A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications

    cs.AI 2025-06 conditional novelty 4.0 of 10

    A survey of 80+ Deep Research systems that proposes a four-layer taxonomy (foundation models, tool use, planning, synthesis) and compares commercial and open-source implementations.

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