Weighting model based on group dynamics to measure convergence in multi-party dialogue

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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.

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APA

Rahimi, Z., & Litman, D. (2018). Weighting model based on group dynamics to measure convergence in multi-party dialogue. In SIGDIAL 2018 - 19th Annual Meeting of the Special Interest Group on Discourse and Dialogue - Proceedings of the Conference (pp. 385–390). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-5046

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