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Main Authors: Hosseinkashi, Yasaman, Tankelevitch, Lev, Pool, Jamie, Cutler, Ross, Madan, Chinmaya
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2304.00652
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author Hosseinkashi, Yasaman
Tankelevitch, Lev
Pool, Jamie
Cutler, Ross
Madan, Chinmaya
author_facet Hosseinkashi, Yasaman
Tankelevitch, Lev
Pool, Jamie
Cutler, Ross
Madan, Chinmaya
contents Workplace meetings are vital to organizational collaboration, yet relatively little progress has been made toward measuring meeting effectiveness and inclusiveness at scale. The recent rise in remote and hybrid meetings represents an opportunity to do so via computer-mediated communication (CMC) systems. Here, we share the results of an effective and inclusive meetings survey embedded within a CMC system in a diverse set of companies and organizations. We correlate the survey results with objective metrics available from the CMC system to identify the generalizable attributes that characterize perceived effectiveness and inclusiveness in meetings. Additionally, we explore a predictive model of meeting effectiveness and inclusiveness based solely on objective meeting attributes. Lastly, we show challenges and discuss solutions around the subjective measurement of meeting experiences. To our knowledge, this is the largest data-driven study conducted after the pandemic peak to measure, understand, and predict effectiveness and inclusiveness in real-world meetings at an organizational scale.
format Preprint
id arxiv_https___arxiv_org_abs_2304_00652
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Meeting effectiveness and inclusiveness: large-scale measurement, identification of key features, and prediction in real-world remote meetings
Hosseinkashi, Yasaman
Tankelevitch, Lev
Pool, Jamie
Cutler, Ross
Madan, Chinmaya
Human-Computer Interaction
Workplace meetings are vital to organizational collaboration, yet relatively little progress has been made toward measuring meeting effectiveness and inclusiveness at scale. The recent rise in remote and hybrid meetings represents an opportunity to do so via computer-mediated communication (CMC) systems. Here, we share the results of an effective and inclusive meetings survey embedded within a CMC system in a diverse set of companies and organizations. We correlate the survey results with objective metrics available from the CMC system to identify the generalizable attributes that characterize perceived effectiveness and inclusiveness in meetings. Additionally, we explore a predictive model of meeting effectiveness and inclusiveness based solely on objective meeting attributes. Lastly, we show challenges and discuss solutions around the subjective measurement of meeting experiences. To our knowledge, this is the largest data-driven study conducted after the pandemic peak to measure, understand, and predict effectiveness and inclusiveness in real-world meetings at an organizational scale.
title Meeting effectiveness and inclusiveness: large-scale measurement, identification of key features, and prediction in real-world remote meetings
topic Human-Computer Interaction
url https://arxiv.org/abs/2304.00652