提出一种衡量对话动态相似性的方法，可更全面评估对话质量。
A Similarity Measure for Comparing Conversational Dynamics
- 基于对话整体互动模式设计动态相似性度量
- 验证了该度量对话题变化的敏感性与鲁棒性
- 适用于研究在线社区中情境权力对对话的影响
对话质量不仅取决于单个回复的质量，更源于这些回复如何共同形成具有独特整体'形态'的交互动态。然而，目前尚无可靠的自动化方法来比较对话的整体动态特征。此类方法可提升对话数据的分析能力，并帮助更全面地评估对话代理。本文提出一种针对对话动态的相似性度量。我们设计了一套验证流程，测试该度量在捕捉对话动态差异方面的鲁棒性及其对对话主题变化的敏感性。为展示其效用，我们利用该度量分析了一个大型在线社区中的对话动态，揭示了情境权力在对话中的作用机制。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。