Time is On My Side: Dynamics of Talk-Time Sharing in Video-chat Conversations

• URL: http://arxiv.org/abs/2506.20474v2
• Date: Fri, 27 Jun 2025 03:08:11 GMT
• Title: Time is On My Side: Dynamics of Talk-Time Sharing in Video-chat Conversations
• Authors: Kaixiang Zhang, Justine Zhang, Cristian Danescu-Niculescu-Mizil,
• Abstract summary: An intrinsic aspect of every conversation is the way talk-time is shared between multiple speakers.<n>We introduce a computational framework for quantifying the conversation-level distribution of talk-time between speakers.<n>We apply this framework to a large dataset of video-chats between strangers.
• Score: 8.063275432999513
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: An intrinsic aspect of every conversation is the way talk-time is shared between multiple speakers. Conversations can be balanced, with each speaker claiming a similar amount of talk-time, or imbalanced when one talks disproportionately. Such overall distributions are the consequence of continuous negotiations between the speakers throughout the conversation: who should be talking at every point in time, and for how long? In this work we introduce a computational framework for quantifying both the conversation-level distribution of talk-time between speakers, as well as the lower-level dynamics that lead to it. We derive a typology of talk-time sharing dynamics structured by several intuitive axes of variation. By applying this framework to a large dataset of video-chats between strangers, we confirm that, perhaps unsurprisingly, different conversation-level distributions of talk-time are perceived differently by speakers, with balanced conversations being preferred over imbalanced ones, especially by those who end up talking less. Then we reveal that -- even when they lead to the same level of overall balance -- different types of talk-time sharing dynamics are perceived differently by the participants, highlighting the relevance of our newly introduced typology. Finally, we discuss how our framework offers new tools to designers of computer-mediated communication platforms, for both human-human and human-AI communication.

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