AcademiaOS: Automating Grounded Theory Development in Qualitative Research with Large Language Models
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 41 references that are in the map. First posted on arXiv 13 Mar 2024.
Builds on
8 of 41 references.
References · 8
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2022Training language models to follow instructions with human feedbackcited by 15,712
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
- 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
- 2022A Survey on In-context Learningcited by 717
- 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 713
- 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Modelscited by 144
- 2023Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generatorscited by 42
Built on by
Citing papers per year: 2026: 1.
1 paper.
- 2026Using Grounded Theory for Agent Behavior Analysis at Scale31 Aug 2026
Similar, not cited
Close in wording, no citation either way
- 2025EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants
- 2023Exploring Qualitative Research Using LLMs
- 2024Thematic Analysis with Open-Source Generative AI and Machine Learning: A New Method for Inductive Qualitative Codebook Development
- 2024Reconciling Methodological Paradigms: Employing Large Language Models as Novice Qualitative Research Assistants in Talent Management Research
- 2026FARS: A Fully Automated Research System Deployed at Scale
- 2024SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories
- 2026Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods
- 2024'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants