A Similarity Measure for Comparing Conversational Dynamics

Fuente: arXiv
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Main Authors: Jung, Sang Min, Zhang, Kaixiang, Danescu-Niculescu-Mizil, Cristian
Format: Preprint
Published: 2025
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author Jung, Sang Min
Zhang, Kaixiang
Danescu-Niculescu-Mizil, Cristian
author_facet Jung, Sang Min
Zhang, Kaixiang
Danescu-Niculescu-Mizil, Cristian
contents The quality of a conversation goes beyond the individual quality of each reply, and instead emerges from how these combine into interactional dynamics that give the conversation its distinctive overall "shape". However, there is no robust automated method for comparing conversations in terms of their overall dynamics. Such methods could enhance the analysis of conversational data and help evaluate conversational agents more holistically. In this work, we introduce a similarity measure for comparing conversations with respect to their dynamics. We design a validation procedure for testing the robustness of the metric in capturing differences in conversation dynamics and for assessing its sensitivity to the topic of the conversations. To illustrate the measure's utility, we use it to analyze conversational dynamics in a large online community, bringing new insights into the role of situational power in conversations.
format Preprint
id arxiv_https___arxiv_org_abs_2507_18956
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Similarity Measure for Comparing Conversational Dynamics
Jung, Sang Min
Zhang, Kaixiang
Danescu-Niculescu-Mizil, Cristian
Computation and Language
The quality of a conversation goes beyond the individual quality of each reply, and instead emerges from how these combine into interactional dynamics that give the conversation its distinctive overall "shape". However, there is no robust automated method for comparing conversations in terms of their overall dynamics. Such methods could enhance the analysis of conversational data and help evaluate conversational agents more holistically. In this work, we introduce a similarity measure for comparing conversations with respect to their dynamics. We design a validation procedure for testing the robustness of the metric in capturing differences in conversation dynamics and for assessing its sensitivity to the topic of the conversations. To illustrate the measure's utility, we use it to analyze conversational dynamics in a large online community, bringing new insights into the role of situational power in conversations.
title A Similarity Measure for Comparing Conversational Dynamics
topic Computation and Language
url https://arxiv.org/abs/2507.18956