mlsanityData to 7 Oct 2026

Large Language Models in Qualitative Research: Uses, Tensions, and Intentions

arXiv 2410.07362 ↗First posted 9 Oct 2024cs.HCcited by 19

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Abstract (arXiv)

Qualitative researchers use tools to collect, sort, and analyze their data. Should qualitative researchers use large language models (LLMs) as part of their practice? LLMs could augment qualitative research, but it is unclear if their use is appropriate, ethical, or aligned with qualitative researchers' goals and values. We interviewed twenty qualitative researchers to investigate these tensions. Many participants see LLMs as promising interlocutors with attractive use cases across the stages of research, but wrestle with their performance and appropriateness. Participants surface concerns regarding the use of LLMs while protecting participant interests, and call attention to an urgent lack of norms and tooling to guide the ethical use of LLMs in research. We document the rapid and broad adoption of LLMs across surfaces, which can interfere with intentional use vital to qualitative research. We use the tensions surfaced by our participants to outline recommendations for researchers considering using LLMs in qualitative research and design principles for LLM-assisted qualitative research tools.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Oct 2024.

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Citing papers per year: 2024: 1; 2025: 7; 2026: 11.

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  1. 2025LOGOS: LLM-driven End-to-End Grounded Theory Development and Schema Induction for Qualitative Researchcited by 6
  2. 2025Show or Tell? Modeling the evolution of request-making in Human-LLM conversationscited by 3
  3. 2025AI Annotation Orchestration: Evaluating LLM verifiers to Improve the Quality of LLM Annotations in Learning Analyticscited by 3
  4. 2026Reflexis: Supporting Reflexivity and Rigor in Collaborative Qualitative Analysis through Design for Deliberationcited by 3
  5. 2025Arti-"fickle" Intelligence: Using LLMs as a Tool for Inference in the Political and Social Sciencescited by 1
  6. 2025Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scalecited by 1
  7. 2026Agent-as-Peer-Debriefer: A Multi-Agent Framework with Perspective-Based Refinement for Qualitative Analysiscited by 1
  8. 2024Collaborative Participatory Research with LLM Agents in South Asia: An Empirically-Grounded Methodological Initiative and Agenda from Field Evidence in Sri Lankacited by 0
  9. 2025Empowering Computing Education Researchers Through LLM-Assisted Content Analysiscited by 0
  10. 2025Can machines perform a qualitative data analysis? Reading the debate with Alan Turingcited by 0
  11. 2026Bridging Human Interpretation and Machine Representation: A Landscape of Qualitative Data Analysis in the LLM Eracited by 0
  12. 2026A conceptual framework for ideology in online discourse beyond the left and rightcited by 0
7 more
  1. 2026LLMs for Qualitative Data Analysis Fail on Security-specificComments in Human Experimentscited by 0
  2. 2026How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Early-Stage Research: A Think-Aloud Studycited by 0
  3. 2026Framing Migration News with LLMs: Structured CoT as a Support for Human Interpretationcited by 0
  4. 2026Will Scaling Improve Social Simulation with LLMs?cited by 0
  5. 2026Validating LLMs in social science: Epistemic threats and emerging normscited by 0
  6. 2026Value-Sensitive Delegation in Everyday AI Agent Use: Evidence from OpenClawcited by 0
  7. 2026Can Vision-Language Models Analyze Human-Centered Video? Mapping Model Capabilities and Human-AI Collaborative Workflowscited by 0