The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research?

Fabian Retkowski, Andreas Sudmann, Alexander Waibel


Abstract
Qualitative research often involves labor-intensive processes that are difficult to scale while preserving analytical depth. This paper introduces The AI Co-Ethnographer (AICoE), a novel end-to-end pipeline developed for qualitative research and designed to move beyond the limitations of simply automating code assignments, offering a more integrated approach. AICoE organizes the entire process, encompassing open coding, code consolidation, code application, and even pattern discovery, leading to a comprehensive analysis of qualitative data.
Anthology ID:
2025.nlp4dh-1.8
Volume:
Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities
Month:
May
Year:
2025
Address:
Albuquerque, USA
Editors:
Mika Hämäläinen, Emily Öhman, Yuri Bizzoni, So Miyagawa, Khalid Alnajjar
Venues:
NLP4DH | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
73–90
Language:
URL:
https://preview.aclanthology.org/fix-sig-urls/2025.nlp4dh-1.8/
DOI:
Bibkey:
Cite (ACL):
Fabian Retkowski, Andreas Sudmann, and Alexander Waibel. 2025. The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research?. In Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities, pages 73–90, Albuquerque, USA. Association for Computational Linguistics.
Cite (Informal):
The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research? (Retkowski et al., NLP4DH 2025)
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PDF:
https://preview.aclanthology.org/fix-sig-urls/2025.nlp4dh-1.8.pdf