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A reappraisal of the uncanny valley: categorical perception or frequency-based sensitization?

Overview of attention for article published in Frontiers in Psychology, January 2015
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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 (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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12 X users
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3 Wikipedia pages

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56 Dimensions

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Title
A reappraisal of the uncanny valley: categorical perception or frequency-based sensitization?
Published in
Frontiers in Psychology, January 2015
DOI 10.3389/fpsyg.2014.01488
Pubmed ID
Authors

Tyler J. Burleigh, Jordan R. Schoenherr

Abstract

The uncanny valley (UCV) hypothesis describes a non-linear relationship between perceived human-likeness and affective response. The "uncanny valley" refers to an intermediate level of human-likeness that is associated with strong negative affect. Recent studies have suggested that the uncanny valley might result from the categorical perception of human-like stimuli during identification. When presented with stimuli sharing human-like traits, participants attempt to segment the continuum in "human" and "non-human" categories. Due to the ambiguity of stimuli located at a category boundary, categorization difficulty gives rise to a strong, negative affective response. Importantly, researchers who have studied the UCV in terms of categorical perception have focused on categorization responses rather than affective ratings. In the present study, we examined whether the negative affect associated with the UCV might be explained in terms of an individual's degree of exposure to stimuli. In two experiments, we tested a frequency-based model against a categorical perception model using a category-learning paradigm. We manipulated the frequency of exemplars that were presented to participants from two categories during a training phase. We then examined categorization and affective responses functions, as well as the relationship between categorization and affective responses. Supporting previous findings, categorization responses suggested that participants acquired novel category structures that reflected a category boundary. These category structures appeared to influence affective ratings of eeriness. Crucially, participants' ratings of eeriness were additionally affected by exemplar frequency. Taken together, these findings suggest that the UCV is determined by both categorical properties as well as the frequency of individual exemplars retained in memory.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 1%
United States 1 1%
Germany 1 1%
Unknown 69 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 19%
Student > Master 13 18%
Student > Bachelor 9 13%
Student > Ph. D. Student 8 11%
Student > Doctoral Student 4 6%
Other 11 15%
Unknown 13 18%
Readers by discipline Count As %
Psychology 20 28%
Neuroscience 6 8%
Computer Science 5 7%
Medicine and Dentistry 5 7%
Social Sciences 5 7%
Other 16 22%
Unknown 15 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 27 January 2024.
All research outputs
#2,780,714
of 22,896,955 outputs
Outputs from Frontiers in Psychology
#5,262
of 30,021 outputs
Outputs of similar age
#41,461
of 352,151 outputs
Outputs of similar age from Frontiers in Psychology
#123
of 394 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 30,021 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done well, scoring higher than 82% 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 352,151 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 394 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.