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

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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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757511
Primary Topic
Digital Communication and Language
Type
article
Field-Weighted Citation Impact
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article

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

Cristian Danescu-Niculescu-Mizil, Kaixiang Zhang, J. Zhang
Proceedings of the ACM on Human-Computer Interaction
Digital Communication and Language
article

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

Cristian Danescu-Niculescu-Mizil, Kaixiang Zhang, J. Zhang
article en

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.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Cornell University (US), University of Michigan (US)
Openalex Percentile: Top 70%
Digital Communication and Language
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