research-article

The design of virtual audiences

Authors:

Willem-Paul Brinkman,

M. Birna van Riemsdijk,

Mark NeerincxAuthors Info & Claims

Computers in Human Behavior, Volume 55, Issue PB

Pages 680 - 694

https://doi.org/10.1016/j.chb.2015.10.008

Published: 01 February 2016 Publication History

Abstract

Expressive virtual audiences are used in scientific research, psychotherapy, and training. To create an expressive virtual audience, developers need to know how specific audience behaviors are associated with certain characteristics of an audience, such as attitude, and how well people can recognize these characteristics. To examine this, four studies were conducted on a virtual audience and its behavioral models: (I) a perception study of a virtual audience showed that people (n = 24) could perceive changes in some of the mood, personality, and attitude parameters of the virtual audience; (II) a design experiment whereby individuals (n = 24) constructed 23 different audience scenarios indicated that the understanding of audience styles was consistent across individuals, and the clustering of similar settings of the virtual audience parameters revealed five distinct generic audience styles; (III) a perception validation study of these five audience styles showed that people (n = 100) could differentiate between some of the styles, and the audience's attentiveness was the most dominating audience characteristic that people perceived; (IV) the examination of the behavioral model of the virtual audience identified several typical audience behaviors for each style. We anticipate that future developers can use these findings to create distinct virtual audiences with recognizable behaviors. Consistency exists across individuals on how audiences behave in various situations.Five generic audience styles exist among 21 different audience scenarios.People can distinguish some generic styles of a virtual audience.Attentiveness is a dominating characteristic of an audience that people can perceive.Specific audience behaviors were identified that made up these five audience styles.

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Cited By

Ristorcelli MD'Ambra APergandi JCasanova ROchs M(2024)Impact of the Nonverbal Behavior of Virtual Audience on Users' Perception of Social AttitudesProceedings of the 2024 International Conference on Advanced Visual Interfaces10.1145/3656650.3656687(1-9)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3656650.3656687
Lugrin JTopel JGlémarec YLugrin BLatoschik MLugrin BLatoschik Mvon Mammen SKopp SPécune FPelachaud C(2023)Posture Parameters for Personality-Enhanced Virtual AudiencesProceedings of the 23rd ACM International Conference on Intelligent Virtual Agents10.1145/3570945.3607311(1-4)Online publication date: 19-Sep-2023
https://dl.acm.org/doi/10.1145/3570945.3607311
Ppali SLalioti VBranch BAng CThomas AWohl BCovaci A(2022)Keep the VRhythm goingProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501922(1-19)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501922
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Index Terms

The design of virtual audiences
1. Human-centered computing
  1. Human computer interaction (HCI)

Index terms have been assigned to the content through auto-classification.

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cover image Computers in Human Behavior

Computers in Human Behavior Volume 55, Issue PB

February 2016

645 pages

ISSN:0747-5632

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Copyright © Elsevier Ltd.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 February 2016

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Cited By

Ristorcelli MD'Ambra APergandi JCasanova ROchs M(2024)Impact of the Nonverbal Behavior of Virtual Audience on Users' Perception of Social AttitudesProceedings of the 2024 International Conference on Advanced Visual Interfaces10.1145/3656650.3656687(1-9)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3656650.3656687
Lugrin JTopel JGlémarec YLugrin BLatoschik MLugrin BLatoschik Mvon Mammen SKopp SPécune FPelachaud C(2023)Posture Parameters for Personality-Enhanced Virtual AudiencesProceedings of the 23rd ACM International Conference on Intelligent Virtual Agents10.1145/3570945.3607311(1-4)Online publication date: 19-Sep-2023
https://dl.acm.org/doi/10.1145/3570945.3607311
Ppali SLalioti VBranch BAng CThomas AWohl BCovaci A(2022)Keep the VRhythm goingProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501922(1-19)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501922
Ehret JBönsch AAspöck LRöhr CBaumann SGrice MFels JKuhlen T(2021)Do Prosody and Embodiment Influence the Perceived Naturalness of Conversational Agents’ Speech?ACM Transactions on Applied Perception10.1145/348658018:4(1-15)Online publication date: 28-Oct-2021
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Barreda-Ángeles MAleix-Guillaume SPereda-Baños A(2020)Users’ psychophysiological, vocal, and self-reported responses to the apparent attitude of a virtual audience in stereoscopic 360°-videoVirtual Reality10.1007/s10055-019-00400-124:2(289-302)Online publication date: 1-Jun-2020
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Glemarec YBosser ABuche CLugrin JLandeck MLatoschik MChollet M(2019)A Scalability Benchmark for a Virtual Audience Perception Model in Virtual RealityProceedings of the 25th ACM Symposium on Virtual Reality Software and Technology10.1145/3359996.3364784(1-1)Online publication date: 12-Nov-2019
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Lugrin JBosser ALatoschik MChollet MGlémarec YLugrin BBrewster SFitzpatrick GCox AKostakos V(2019)Towards Narrative-Driven Atmosphere for Virtual ClassroomsExtended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290607.3313067(1-6)Online publication date: 2-May-2019
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Lugrin JCharles FHabel MMatthews JDudaczy HOberdörfer SWittmann ASeufert CPorteous JGrafe SLatoschik MAndre EKoenig SDastani MSukthankar G(2018)Benchmark Framework for Virtual Students' BehavioursProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3238133(2236-2238)Online publication date: 9-Jul-2018
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