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Gelotophobia and the Challenges of Implementing Laughter into Virtual Agents Interactions

Overview of attention for article published in Frontiers in Human Neuroscience, November 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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1 blog
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8 X users
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1 Facebook page

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42 Mendeley
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1 CiteULike
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Title
Gelotophobia and the Challenges of Implementing Laughter into Virtual Agents Interactions
Published in
Frontiers in Human Neuroscience, November 2014
DOI 10.3389/fnhum.2014.00928
Pubmed ID
Authors

Willibald F. Ruch, Tracey Platt, Jennifer Hofmann, Radosław Niewiadomski, Jérôme Urbain, Maurizio Mancini, Stéphane Dupont

Abstract

This study investigated which features of AVATAR laughter are perceived threatening for individuals with a fear of being laughed at (gelotophobia), and individuals with no gelotophobia. Laughter samples were systematically varied (e.g., intensity, laughter pitch, and energy for the voice, intensity of facial actions of the face) in three modalities: animated facial expressions, synthesized auditory laughter vocalizations, and motion capture generated puppets displaying laughter body movements. In the online study 123 adults completed, the GELOPH <15 > (Ruch and Proyer, 2008a,b) and rated randomly presented videos of the three modalities for how malicious, how friendly, how real the laughter was (0 not at all to 8 extremely). Additionally, an open question asked which markers led to the perception of friendliness/maliciousness. The current study identified features in all modalities of laughter stimuli that were perceived as malicious in general, and some that were gelotophobia specific. For facial expressions of AVATARS, medium intensity laughs triggered highest maliciousness in the gelotophobes. In the auditory stimuli, the fundamental frequency modulations and the variation in intensity were indicative of maliciousness. In the body, backwards and forward movements and rocking vs. jerking movements distinguished the most malicious from the least malicious laugh. From the open answers, the shape and appearance of the lips curling induced feelings that the expression was malicious for non-gelotophobes and that the movement round the eyes, elicited the face to appear as friendly. This was opposite for gelotophobes. Gelotophobia savvy AVATARS should be of high intensity, containing lip and eye movements and be fast, non-repetitive voiced vocalization, variable and of short duration. It should not contain any features that indicate a down-regulation in the voice or body, or indicate voluntary/cognitive modulation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 21%
Student > Bachelor 7 17%
Student > Master 6 14%
Researcher 3 7%
Student > Postgraduate 2 5%
Other 3 7%
Unknown 12 29%
Readers by discipline Count As %
Psychology 14 33%
Medicine and Dentistry 4 10%
Computer Science 3 7%
Linguistics 1 2%
Nursing and Health Professions 1 2%
Other 3 7%
Unknown 16 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 08 March 2018.
All research outputs
#2,094,156
of 24,312,464 outputs
Outputs from Frontiers in Human Neuroscience
#992
of 7,461 outputs
Outputs of similar age
#29,318
of 371,941 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#36
of 209 outputs
Altmetric has tracked 24,312,464 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,461 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.8. This one has done well, scoring higher than 86% 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 371,941 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 92% of its contemporaries.
We're also able to compare this research output to 209 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.