HCAIIRMar 13, 2024

AcademiaOS: Automating Grounded Theory Development in Qualitative Research with Large Language Models

arXiv:2403.08844v13 citationsh-index: 3Has Code
Originality Incremental advance
AI Analysis

This addresses the problem of automating qualitative analysis for researchers, but it is a first attempt and likely incremental in applying existing LLM capabilities.

The paper tackles automating grounded theory development in qualitative research using large language models, with a user study (n=19) showing acceptance and potential to augment humans.

AcademiaOS is a first attempt to automate grounded theory development in qualitative research with large language models. Using recent large language models' language understanding, generation, and reasoning capabilities, AcademiaOS codes curated qualitative raw data such as interview transcripts and develops themes and dimensions to further develop a grounded theoretical model, affording novel insights. A user study (n=19) suggests that the system finds acceptance in the academic community and exhibits the potential to augment humans in qualitative research. AcademiaOS has been made open-source for others to build upon and adapt to their use cases.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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