Reflections on Inductive Thematic Saturation as a potential metric for measuring the validity of an inductive Thematic Analysis with LLMs
Not on the map. Why?
Abstract (arXiv)
This paper presents a set of reflections on saturation and the use of Large Language Models (LLMs) for performing Thematic Analysis (TA). The paper suggests that initial thematic saturation (ITS) could be used as a metric to assess part of the transactional validity of TA with LLM, focusing on the initial coding. The paper presents the initial coding of two datasets of different sizes, and it reflects on how the LLM reaches some form of analytical saturation during the coding. The procedure proposed in this work leads to the creation of two codebooks, one comprising the total cumulative initial codes and the other the total unique codes. The paper proposes a metric to synthetically measure ITS using a simple mathematical calculation employing the ratio between slopes of cumulative codes and unique codes. The paper contributes to the initial body of work exploring how to perform qualitative analysis with LLMs.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 12 of its 47 references that are in the map. First posted on arXiv 6 Jan 2024.
Builds on
12 of 47 references.
References · 12
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2023Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Codingcited by 82
- 2023LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Codingcited by 64
- 2023CoAIcoder: Examining the Effectiveness of AI-assisted Human-to-Human Collaboration in Qualitative Analysiscited by 25
- 2023Using Large Language Models to Support Thematic Analysis in Empirical Legal Studiescited by 25
- 2023Shaping the Emerging Norms of Using Large Language Models in Social Computing Researchcited by 14
- 2023Writing user personas with Large Language Models: Testing phase 6 of a Thematic Analysis of semi-structured interviewscited by 7
- 2020Theory In, Theory Out: The uses of social theory in machine learning for social sciencecited by 4
- 2021Qualitative Analysis for Human Centered AIcited by 4
- 2023Algorithmic failure as a humanities methodology: machine learning's mispredictions identify rich cases for qualitative analysiscited by 3
- 2023Critical-Reflective Human-AI Collaboration: Exploring Computational Tools for Art Historical Image Retrievalcited by 2
- 2022Theme and Topic: How Qualitative Research and Topic Modeling Can Be Brought Togethercited by 1
Built on by
Citing papers per year: 2024: 1; 2025: 3; 2026: 2.
6 papers.
- 2024A Computational Method for Measuring "Open Codes" in Qualitative Analysiscited by 6
- 2025Codebook Reduction and Saturation: Novel observations on Inductive Thematic Saturation for Large Language Models and initial coding in Thematic Analysiscited by 3
- 2025Can machines perform a qualitative data analysis? Reading the debate with Alan Turingcited by 0
- 2025Multi-LLM Thematic Analysis with Dual Reliability Metrics: Combining Cohen's Kappa and Semantic Similarity for Qualitative Research Validationcited by 0
- 2026Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narrativescited by 0
- 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
- 2026Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives22 Apr 2026
- 2025Multi-LLM Thematic Analysis with Dual Reliability Metrics: Combining Cohen's Kappa and Semantic Similarity for Qualitative Research Validation23 Dec 2025
- 2025Can machines perform a qualitative data analysis? Reading the debate with Alan Turing2 Dec 2025
- 2025Codebook Reduction and Saturation: Novel observations on Inductive Thematic Saturation for Large Language Models and initial coding in Thematic Analysis6 Mar 2025
- 2024A Computational Method for Measuring "Open Codes" in Qualitative Analysis19 Nov 2024