The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Categorization difficulty is associated with negative evaluation in the “uncanny valley” phenomenon
Open accessAbstract
Abstract Human observers often experience strongly negative impressions of human‐like objects falling within a particular range of visual similarity to real humans (the “uncanny valley” phenomenon). We hypothesized that negative impressions in the uncanny valley phenomenon are related to a difficulty in object categorization. We produced stimulus images by morphing two of each of real, stuffed, and cartoon human face images (Experiment 1). Observers were asked to categorize each of these images as either category and evaluated the likability of the image. The results revealed that the longest latency, the highest ambiguity in categorization, and the lowest likability score co‐occurred at consistent morphing percentages. Similar results were obtained even when we employed stimulus images that were created by morphing two of each of real, stuffed, and cartoon dog images (Experiment 2). However, the effect of categorization difficulty on evaluation was weak when two real human faces were morphed (Experiment 3). These results suggest that the difficulty in categorizing an object as either of two dissimilar categories is linked to negative evaluation regardless of whether the object is human‐related or not.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Hence, it is possible that the lower pleasantness ratings for intermediate morphs could have resulted from morphing artifacts rather than intermediate human-likeness level.”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as Yamada et al., 2013
In the citing paper
“One of the studies in Table 4 (Yamada et al., 2013) was excluded from the total count because of plausible morphing artifacts.”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as Yamada et al., 2013
In the citing paper
“One image morphing study (Yamada et al., 2013) demonstrated that the slowest identification task response times and the most negative likability evaluations coincided with each other; however, these results were excluded because the likability evaluations could plausibly have been influenced by morphing artifacts (cf. Section Naïve and Morbidity Hypotheses).”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as Yamada et al., 2013
In the citing paper
“Consistently, two participants in this study had reported spontaneously after the experiment that “they [had] evaluated the likability of the images based on the presence or absence of morphing noise” (ibid., 4).”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as Yamada et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Basic objects in natural categories
Rosch, E., Mervis, C. B., Gray, W. D., Johnson, D. M., & Boyes-Braem, P. (1976) · Cognitive Psychology · doi:10.1016/0010-0285(76)90013-x · Cited by 5,643
The Emotional Brain: The Mysterious Underpinnings of Emotional Life
LeDoux, J. E. (2004) · Medical Entomology and Zoology · Cited by 4,212
Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver's Processing Experience?
Reber, R., Schwarz, N., & Winkielman, P. (2004) · Personality and Social Psychology Review · doi:10.1207/s15327957pspr0804_3 · Cited by 3,149
Context theory of classification learning
Medin, D. L., & Schaffer, M. M. (1978) · Psychological Review · doi:10.1037/0033-295x.85.3.207 · Cited by 3,061
The psychometric function: I. Fitting, sampling, and goodness of fit
Wichmann, F. A., & Hill, N. J. (2001) · Perception & Psychophysics · doi:10.3758/bf03194544 · Cited by 2,359
Rozin, P. N., & Fallon, A. E. (1987) · Psychological Review · doi:10.1037/0033-295x.94.1.23 · Cited by 1,742
The Emotional Brain: The Mysterious Underpinnings of Emotional Life
Paradiso, S. (1998) · American Journal of Psychiatry · doi:10.1176/ajp.155.4.570 · Cited by 1,674
(1987) · PubMed · Cited by 1,496
Bukimi no tani [the uncanny valley]
Mori, M. (1970) · Energy · Cited by 1,485
Effects of Perceptual Fluency on Affective Judgments
Reber, R., Winkielman, P., & Schwarz, N. (1998) · Psychological Science · doi:10.1111/1467-9280.00008 · Cited by 1,390
Attractive Faces Are Only Average
Langlois, J. H., & Roggman, L. A. (1990) · Psychological Science · doi:10.1111/j.1467-9280.1990.tb00079.x · Cited by 1,339
Pattern recognition and categorization
Reed, S. K. (1972) · Cognitive Psychology · doi:10.1016/0010-0285(72)90014-x · Cited by 1,002
The psychometric function: II. Bootstrap-based confidence intervals and sampling
Wichmann, F. A., & Hill, N. J. (2001) · Perception & Psychophysics · doi:10.3758/bf03194545 · Cited by 809
Varieties of perceptual independence.
Ashby, F. G., & Townsend, J. T. (1986) · Psychological Review · doi:10.1037/0033-295x.93.2.154 · Cited by 726
Cascade processes in picture identification
Humphreys, G. W., Riddoch, M. J., & Quinlan, P. T. (1988) · Cognitive Neuropsychology · doi:10.1080/02643298808252927 · Cited by 709
Significance tests for multiple comparison of proportions, variances, and other statistics.
Ryan, T. H. (1960) · Psychological Bulletin · doi:10.1037/h0044320 · Cited by 685
The uncanny advantage of using androids in cognitive and social science research
MacDorman, K. F., & Ishiguro, H. (2006) · Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems · doi:10.1075/is.7.3.03mac · Cited by 658
The Uncanny Valley: Effect of Realism on the Impression of Artificial Human Faces
Seyama, J., & Nagayama, R. S. (2007) · PRESENCE Virtual and Augmented Reality · doi:10.1162/pres.16.4.337 · Cited by 583
Decision rules in the perception and categorization of multidimensional stimuli.
Ashby, F. G., & Gott, R. E. (1988) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037//0278-7393.14.1.33 · Cited by 539
Walters, M. L., Syrdal, D. S., Dautenhahn, K., Boekhorst, R. T., & Koay, K. L. (2007) · Autonomous Robots · doi:10.1007/s10514-007-9058-3 · Cited by 449
What Is Average and What Is Not Average About Attractive Faces?
Langlois, J. H., Roggman, L. A., & Musselman, L. (1994) · Psychological Science · doi:10.1111/j.1467-9280.1994.tb00503.x · Cited by 373
Decision rules in the perception and categorization of multidimensional stimuli.
Ashby, F. G., & Gott, R. E. (1988) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.14.1.33 · Cited by 328
Paradiso, S., Johnson, D. L., Andreasen, N. C., OʼLeary, D. S., Watkins, G. L., Ponto, L. L. B., & Hichwa, R. D. (1999) · American Journal of Psychiatry · doi:10.1176/ajp.156.10.1618 · Cited by 310
Category Specificity in Brain and Mind
(2005) · Psychology Press eBooks · doi:10.4324/9780203990292 · Cited by 233
Monkey visual behavior falls into the uncanny valley
Steckenfinger, S. A., & Ghazanfar, A. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0910063106 · Cited by 180
Human emotion and the uncanny valley
Ho, C.-C., MacDorman, K. F., & Pramono, Z. A. D. (2008) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1349822.1349845 · Cited by 149
Pupillary responses in art appreciation: Effects of aesthetic emotions.
Kuchinke, L., Trapp, S., Jacobs, A. M., & Leder, H. (2009) · Psychology of Aesthetics Creativity and the Arts · doi:10.1037/a0014464 · Cited by 91
Facial Averageness and Attractiveness in an Isolated Population of Hunter-Gatherers
Apicella, C. L., Little, A. C., & Marlowe, F. W. (2007) · Perception · doi:10.1068/p5601 · Cited by 90
Research works printed but not linked: 6
- Hanson D.(2006).Exploring the aesthetic range for humanoid robots. InK.MacDorman&H.Ishiguro(Eds.) Proceedings of the ICCS/CogSci‐2006 Symposium: Toward Social Mechanisms of Android Science pp.16–20.
- MacDorman K. F.(2005).Androids as experimental apparatus: Why is there an uncanny valley and can we exploit it?CogSci‐2005 Workshop: Toward Social Mechanisms of Android Science pp.108–118.
- Matsumoto D., 1988, Japanese and Caucasian facial expressions of emotion and neutral faces (JACFEE and JACNeuF)
- Mori M., 1970, The uncanny valley, Energy, 7, 33
- Ramey C. H.(2005).The uncanny valley of similarities concerning abortion baldness heaps of sand and humanlike robots.Proceedings of the Views of the Uncanny Valley Workshop IEEE‐RAS International Conference on Humanoid Robots pp.8–13.
- Schultz C. M., 2004, The complete Peanuts 1950–1952. Vol. 1
Cited by
Sorted by citations
Kätsyri, J., Förger, K., Mäkäräinen, M., & Takala, T. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00390 · Cited by 500
Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley
Mathur, M. B., & Reichling, D. B. (2016) · Cognition · doi:10.1016/j.cognition.2015.09.008 · Cited by 439
Franke, C., Groeppel-Klein, A., & Müller, K. (2023) · Journal of Advertising · doi:10.1080/00913367.2022.2154721 · Cited by 408
The Uncanny Valley: Existence and Explanations
Wang, S., Lilienfeld, S. O., & Rochat, P. (2015) · Review of General Psychology · doi:10.1037/gpr0000056 · Cited by 357
Stein, J., & Ohler, P. (2016) · Cognition · doi:10.1016/j.cognition.2016.12.010 · Cited by 297
Metadata
- Authors
- YAMADA, Y., KAWABE, T., & IHAYA, K.
- Affiliations
- Yamaguchi University (JP)
- NTT (Japan) (JP)
- Kyushu University (JP)
- Corresponding author
- YAMADA, YUKI
- Venue
- Japanese Psychological Research
- Publisher
- Wiley
- Published
- 2012-09-03
- Volume
- 55
- Issue
- 1
- Pages
- 20-32
- ISSN
- 0021-5368 (ISSN-L)
- 1468-5884
- OpenAlex
- W2122384877
- Cited by
- 170
- References
- 28
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 16 · 2023: 12 · 2022: 13 · 2021: 17 · 2020: 13 · 2019: 16 · 2018: 8 · 2017: 13 · 2016: 8 · 2015: 13 · 2014: 4 · 2013: 3
- FWCI
- 3.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Japanese Psychological Research (publishedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion)
- Kyushu University Institutional Repository (QIR) (Kyushu University) (submittedVersion, other-oa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
- Keywords
- uncanny valley, negative evaluation, face perception, likeability, cartoon faces, stuffed animals, dogs
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
