mlsanityData to 14 Oct 2026

Reflections on Inductive Thematic Saturation as a potential metric for measuring the validity of an inductive Thematic Analysis with LLMs

arXiv 2401.03239 ↗First posted 6 Jan 2024cs.CL cs.CYcited by 6

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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

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2023Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Codingcited by 82
  3. 2023LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Codingcited by 64
  4. 2023CoAIcoder: Examining the Effectiveness of AI-assisted Human-to-Human Collaboration in Qualitative Analysiscited by 25
  5. 2023Using Large Language Models to Support Thematic Analysis in Empirical Legal Studiescited by 25
  6. 2023Shaping the Emerging Norms of Using Large Language Models in Social Computing Researchcited by 14
  7. 2023Writing user personas with Large Language Models: Testing phase 6 of a Thematic Analysis of semi-structured interviewscited by 7
  8. 2020Theory In, Theory Out: The uses of social theory in machine learning for social sciencecited by 4
  9. 2021Qualitative Analysis for Human Centered AIcited by 4
  10. 2023Algorithmic failure as a humanities methodology: machine learning's mispredictions identify rich cases for qualitative analysiscited by 3
  11. 2023Critical-Reflective Human-AI Collaboration: Exploring Computational Tools for Art Historical Image Retrievalcited by 2
  12. 2022Theme and Topic: How Qualitative Research and Topic Modeling Can Be Brought Togethercited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 2.

6 papers.