A Similarity Measure for Comparing Conversational Dynamics
This provides a tool for researchers and developers to analyze conversational data and evaluate conversational agents more holistically, though it is incremental as it builds on existing work in conversation analysis.
The authors tackled the problem of comparing conversations based on their overall dynamics, introducing a similarity measure and validating it to capture differences and topic sensitivity, which they applied to analyze situational power in a large online community.
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.