@inproceedings{jung-etal-2025-similarity,
    title = "A Similarity Measure for Comparing Conversational Dynamics",
    author = "Jung, Sang Min  and
      Zhang, Kaixiang  and
      Danescu-Niculescu-Mizil, Cristian",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-luhme/2025.findings-emnlp.1327/",
    doi = "10.18653/v1/2025.findings-emnlp.1327",
    pages = "24416--24447",
    ISBN = "979-8-89176-335-7",
    abstract = "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."
}