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

Fuente: arXiv
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Autore principale: Übellacker, Thomas
Natura: Preprint
Pubblicazione: 2024
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author Übellacker, Thomas
author_facet Übellacker, Thomas
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_08844
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AcademiaOS: Automating Grounded Theory Development in Qualitative Research with Large Language Models
Übellacker, Thomas
Human-Computer Interaction
Artificial Intelligence
Information Retrieval
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.
title AcademiaOS: Automating Grounded Theory Development in Qualitative Research with Large Language Models
topic Human-Computer Interaction
Artificial Intelligence
Information Retrieval
url https://arxiv.org/abs/2403.08844