@inproceedings{karan-etal-2023-leda,
title = "{LEDA}: a Large-Organization Email-Based Decision-Dialogue-Act Analysis Dataset",
author = "Karan, Mladen and
Khare, Prashant and
Shekhar, Ravi and
McQuistin, Stephen and
Castro, Ignacio and
Tyson, Gareth and
Perkins, Colin and
Healey, Patrick and
Purver, Matthew",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.378",
doi = "10.18653/v1/2023.findings-acl.378",
pages = "6080--6089",
abstract = "Collaboration increasingly happens online. This is especially true for large groups working on global tasks, with collaborators all around the globe. The size and distributed nature of such groups makes 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 organisation {--} 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 organisations. Finally, we experiment with a preliminary transformer-based dialog act tagging model.",
}
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<abstract>Collaboration increasingly happens online. This is especially true for large groups working on global tasks, with collaborators all around the globe. The size and distributed nature of such groups makes 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 organisation – 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 organisations. Finally, we experiment with a preliminary transformer-based dialog act tagging model.</abstract>
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%0 Conference Proceedings
%T LEDA: a Large-Organization Email-Based Decision-Dialogue-Act Analysis Dataset
%A Karan, Mladen
%A Khare, Prashant
%A Shekhar, Ravi
%A McQuistin, Stephen
%A Castro, Ignacio
%A Tyson, Gareth
%A Perkins, Colin
%A Healey, Patrick
%A Purver, Matthew
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Findings of the Association for Computational Linguistics: ACL 2023
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F karan-etal-2023-leda
%X Collaboration increasingly happens online. This is especially true for large groups working on global tasks, with collaborators all around the globe. The size and distributed nature of such groups makes 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 organisation – 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 organisations. Finally, we experiment with a preliminary transformer-based dialog act tagging model.
%R 10.18653/v1/2023.findings-acl.378
%U https://aclanthology.org/2023.findings-acl.378
%U https://doi.org/10.18653/v1/2023.findings-acl.378
%P 6080-6089
Markdown (Informal)
[LEDA: a Large-Organization Email-Based Decision-Dialogue-Act Analysis Dataset](https://aclanthology.org/2023.findings-acl.378) (Karan et al., Findings 2023)
ACL
- Mladen Karan, Prashant Khare, Ravi Shekhar, Stephen McQuistin, Ignacio Castro, Gareth Tyson, Colin Perkins, Patrick Healey, and Matthew Purver. 2023. LEDA: a Large-Organization Email-Based Decision-Dialogue-Act Analysis Dataset. In Findings of the Association for Computational Linguistics: ACL 2023, pages 6080–6089, Toronto, Canada. Association for Computational Linguistics.