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Automated mapping of competitive and collaborative overlapping talk in video meetings

Lookup NU author(s): Lenia MargaritiORCiD

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2022.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

Video meetings are notorious for difficulties with conversational turn-taking, which has impacts on inclusion and outcomes. We present a scalable automatic process to categorize turn-taking patterns in remote meetings based on eyes-off analysis of meeting transcripts. Drawing on a series of remote meetings (10 series, 34 total meetings) recorded in July-August 2021 by employees of a global technology company, we identified and parametrized patterns of cooperative and competitive overlaps of turns. The results show initial success characterizing people’s behaviours as either likely to continue or cede turns based on either the amount of overlap that they produce during other’s turns or the amount of overlap they experience in their own turns. With further development and validation, this method could be used to measure inclusion in remote and hybrid meetings.


Publication metadata

Author(s): Margariti E, Rintel S, Murphy B, Sellen A

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems

Year of Conference: 2022

Pages: Article no.: 311

Online publication date: 28/02/2022

Acceptance date: 18/02/2022

Date deposited: 27/02/2023

Publisher: ACM

URL: https://doi.org/10.1145/3491101.3519612

DOI: 10.1145/3491101.3519612

ePrints DOI: 10.57711/6zxf-9s04

Library holdings: Search Newcastle University Library for this item

ISBN: 9781450391566


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