research-article

Social engagement in public places: a tale of one robot

Authors:

Lilia Moshkina,

Susan Trickett,

J. Gregory TraftonAuthors Info & Claims

HRI '14: Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction

Pages 382 - 389

https://doi.org/10.1145/2559636.2559678

Published: 03 March 2014 Publication History

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Abstract

In this paper, we describe a large-scale (over 4000 participants) observational field study at a public venue, designed to explore how social a robot needs to be for people to engage with it. In this study we examined a prediction of Computers Are Social Actors (CASA) framework: the more machines present human-like characteristics in a consistent manner, the more likely they are to invoke a social response. Our humanoid robot's behavior varied in the amount of social cues, from no active social cues to increasing levels of social cues during story-telling to human-like game-playing interaction. We found several strong aspects of support for CASA: the robot that provides even minimal social cues (speech) is more engaging than a robot that does nothing, and the more human-like the robot behaved during story-telling, the more social engagement was observed. However, contrary to the prediction, the robot's game-playing did not elicit more engagement than other, less social behaviors.

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Stefanov KNakano YKobayashi CHoshina ISakato TNihei FTakayama CIshii RTsujii M(2024)Participation Role-Driven Engagement Estimation of ASD Individuals in Neurodiverse Group DiscussionsProceedings of the 26th International Conference on Multimodal Interaction10.1145/3678957.3685721(556-564)Online publication date: 4-Nov-2024
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Erel HVázquez MSebo SSalomons NGillet SScassellati B(2024)RoSI: A Model for Predicting Robot Social InfluenceACM Transactions on Human-Robot Interaction10.1145/364151513:2(1-22)Online publication date: 14-Jun-2024
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Index Terms

Social engagement in public places: a tale of one robot
1. Social and professional topics
  1. Computing / technology policy

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Information & Contributors

Information

Published In

HRI '14: Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction

March 2014

538 pages

ISBN:9781450326582

DOI:10.1145/2559636

General Chairs:
Gerhard Sagerer
Bielefeld University, Germany
,
Michita Imai
Keio University, Japan
,
Program Chairs:
Tony Belpaeme
Plymouth University, UK
,
Andrea Thomaz
Georgia Institute of Technology, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 March 2014

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HRI'14

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HRI'14: ACM/IEEE International Conference on Human-Robot Interaction

March 3 - 6, 2014

Bielefeld, Germany

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HRI '14 Paper Acceptance Rate 32 of 132 submissions, 24%;

Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Stefanov KNakano YKobayashi CHoshina ISakato TNihei FTakayama CIshii RTsujii M(2024)Participation Role-Driven Engagement Estimation of ASD Individuals in Neurodiverse Group DiscussionsProceedings of the 26th International Conference on Multimodal Interaction10.1145/3678957.3685721(556-564)Online publication date: 4-Nov-2024
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Erel HVázquez MSebo SSalomons NGillet SScassellati B(2024)RoSI: A Model for Predicting Robot Social InfluenceACM Transactions on Human-Robot Interaction10.1145/364151513:2(1-22)Online publication date: 14-Jun-2024
https://dl.acm.org/doi/10.1145/3641515
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