LEDA: a Large-Organization Email-Based Decision-Dialogue-Act Analysis Dataset

Mladen Karan, Prashant Khare, Ravi Shekhar, Stephen McQuistin, Colin Perkins, Ignacio Castro, Gareth Tyson, Patrick Healey, Matthew Purver

Research output: Contribution to conferencePaperpeer-review


Collaboration increasingly happens online. This is especially true for large groups working on global tasks, with collaborators all around the world. The size and distributed nature of such groups make decision-making challenging. This paper proposes a set of dialog acts for the study of decision-making mechanisms in such groups, and provides a new annotated dataset based on real-world data from the public mail-archives of one such organization – the Internet Engineering Task Force (IETF). We provide an initial data analysis showing that this dataset can be used to better understand decision-making in such organizations. Finally, we experiment with a preliminary transformer-based dialog act tagging model.
Original languageEnglish
Publication statusPublished - 9 Jul 2023
EventFindings of the Association for Computational Linguistics - Toronto, Canada
Duration: 9 Jul 202314 Jul 2023


ConferenceFindings of the Association for Computational Linguistics
Abbreviated titleACL
Internet address


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