Weighting Model Based on Group Dynamics to Measure Convergence in Multi-party Dialogue

Zahra Rahimi, Diane Litman


Abstract
This paper proposes a new weighting method for extending a dyad-level measure of convergence to multi-party dialogues by considering group dynamics instead of simply averaging. Experiments indicate the usefulness of the proposed weighted measure and also show that in general a proper weighting of the dyad-level measures performs better than non-weighted averaging in multiple tasks.
Anthology ID:
W18-5046
Volume:
Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Kazunori Komatani, Diane Litman, Kai Yu, Alex Papangelis, Lawrence Cavedon, Mikio Nakano
Venue:
SIGDIAL
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
385–390
Language:
URL:
https://aclanthology.org/W18-5046
DOI:
10.18653/v1/W18-5046
Bibkey:
Cite (ACL):
Zahra Rahimi and Diane Litman. 2018. Weighting Model Based on Group Dynamics to Measure Convergence in Multi-party Dialogue. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 385–390, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Weighting Model Based on Group Dynamics to Measure Convergence in Multi-party Dialogue (Rahimi & Litman, SIGDIAL 2018)
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PDF:
https://preview.aclanthology.org/ingest-acl-2023-videos/W18-5046.pdf