A Similarity Measure for Comparing Conversational Dynamics
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908548868341760 |
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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 |