Extending the Discourse Analysis Tool Suite with Whiteboards for Visual Qualitative Analysis

Tim Fischer, Florian Schneider, Fynn Petersen-Frey, Anja Silvia Mollah Haque, Isabel Eiser, Gertraud Koch, Chris Biemann

Abstract
In this system demonstration paper, we describe the Whiteboards extension for an existing web-based platform for digital qualitative discourse analysis. Whiteboards comprise interactive graph-based interfaces to organize and manipulate objects, which can be qualitative research data, such as documents, images, etc., and analyses of these research data, such as annotations, tags, and code structures. The proposed extension offers a customizable view of the material and a wide range of actions that enable new ways of interacting and working with such resources. We show that the visualizations facilitate various use cases of qualitative data analysis, including reflection of the research process through sampling maps, creation of actor networks, and refining code taxonomies.
Anthology ID:
2024.lrec-main.615
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
7017–7022
Language:
URL:
https://aclanthology.org/2024.lrec-main.615
DOI:
Bibkey:
Cite (ACL):
Tim Fischer, Florian Schneider, Fynn Petersen-Frey, Anja Silvia Mollah Haque, Isabel Eiser, Gertraud Koch, and Chris Biemann. 2024. Extending the Discourse Analysis Tool Suite with Whiteboards for Visual Qualitative Analysis. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7017–7022, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Extending the Discourse Analysis Tool Suite with Whiteboards for Visual Qualitative Analysis (Fischer et al., LREC-COLING 2024)
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