Perceived Conversation Quality in Spontaneous Interactions

July 12, 2022 Β· Declared Dead Β· πŸ› IEEE Transactions on Affective Computing

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Authors Chirag Raman, Navin Raj Prabhu, Hayley Hung arXiv ID 2207.05791 Category cs.HC: Human-Computer Interaction Cross-listed cs.MM Citations 8 Venue IEEE Transactions on Affective Computing Last Checked 4 months ago
Abstract
The quality of daily spontaneous conversations is of importance towards both our well-being as well as the development of interactive social agents. Prior research directly studying the quality of social conversations has operationalized it in narrow terms, associating greater quality to less small talk. Other works taking a broader perspective of interaction experience have indirectly studied quality through one of the several overlapping constructs such as rapport or engagement, in isolation. In this work we bridge this gap by proposing a holistic conceptualization of conversation quality, building upon the collaborative attributes of cooperative conversation floors. Taking a multilevel perspective of conversation, we develop and validate two instruments for perceived conversation quality (PCQ) at the individual and group levels. Specifically, we motivate capturing external raters' gestalt impressions of participant experiences from thin slices of behavior, and collect annotations of PCQ on the publicly available MatchNMingle dataset of in-the-wild mingling conversations. Finally, we present an analysis of behavioral features that are predictive of PCQ. We find that for the conversations in MatchNMingle, raters tend to associate smaller group sizes, equitable speaking turns with fewer interruptions, and time taken for synchronous bodily coordination with higher PCQ.
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