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Toward understanding social cues and signals in human–robot interaction: effects of robot gaze and proxemic behavior

Overview of attention for article published in Frontiers in Psychology, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

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1 news outlet
twitter
6 X users
googleplus
1 Google+ user

Citations

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105 Dimensions

Readers on

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256 Mendeley
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Title
Toward understanding social cues and signals in human–robot interaction: effects of robot gaze and proxemic behavior
Published in
Frontiers in Psychology, January 2013
DOI 10.3389/fpsyg.2013.00859
Pubmed ID
Authors

Stephen M. Fiore, Travis J. Wiltshire, Emilio J. C. Lobato, Florian G. Jentsch, Wesley H. Huang, Benjamin Axelrod

Abstract

As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human-robot interaction (HRI). We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot Ava(TM) mobile robotics platform in a hallway navigation scenario. Cues associated with the robot's proxemic behavior were found to significantly affect participant perceptions of the robot's social presence and emotional state while cues associated with the robot's gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot's mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 256 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Germany 2 <1%
United States 2 <1%
Spain 2 <1%
Portugal 1 <1%
Sweden 1 <1%
Indonesia 1 <1%
Hungary 1 <1%
France 1 <1%
Other 0 0%
Unknown 243 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 68 27%
Student > Master 49 19%
Student > Bachelor 24 9%
Researcher 23 9%
Student > Doctoral Student 15 6%
Other 36 14%
Unknown 41 16%
Readers by discipline Count As %
Computer Science 62 24%
Psychology 61 24%
Engineering 33 13%
Social Sciences 12 5%
Design 11 4%
Other 28 11%
Unknown 49 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 April 2020.
All research outputs
#2,548,888
of 26,368,346 outputs
Outputs from Frontiers in Psychology
#5,097
of 35,255 outputs
Outputs of similar age
#23,525
of 294,355 outputs
Outputs of similar age from Frontiers in Psychology
#219
of 967 outputs
Altmetric has tracked 26,368,346 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 35,255 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 294,355 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 967 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.