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The uncanny valley hypothesis (UVH) suggests that almost, but not fully, humanlike artificial characters elicit a feeling of eeriness or discomfort in observers. This study used Natural Language Processing of YouTube comments to provide ecologically-valid, non-laboratory results about people’s emotional reactions toward robots. It contains analyses of 224,544 comments from 1515 videos showing robots from a wide humanlikeness spectrum. The humanlikeness scores were acquired from the Anthropomorphic roBOT database. The analysis showed that people use words related to eeriness to describe very humanlike robots. Humanlikeness was linearly related to both general sentiment and perceptions of eeriness—-more humanlike robots elicit more negative emotions. One of the subscales of humanlikeness, Facial Features, showed a UVH-like relationship with both sentiment and eeriness. The exploratory analysis demonstrated that the most suitable words for measuring the self-reported uncanny valley effect are: ‘scary’ and ‘creepy’. In contrast to theoretical expectations, the results showed that humanlikeness was not related to either pleasantness or attractiveness. Finally, it was also found that the size of robots influences sentiment toward the robots. According to the analysis, the reason behind this is the perception of smaller robots as more playable (as toys), although the prediction that bigger robots would be perceived as more threatening was not supported.

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The uncanny valley (UV) hypothesis suggests that the observation of almost human-like characters causes an increase of discomfort. We conducted a study using self-report questionnaire, response time measurement, and electrodermal activity (EDA) evaluation. In the study, 12 computer-generated characters (robots, androids, animated, and human characters) were presented to 33 people (17 women) to (1) test the effect of a background context on the perception of characters, (2) establish whether there is a relation between declared feelings and physiological arousal, and (3) detect the valley of the presented stimuli. The findings provide support for reverse relation between human-likeness and the arousal (EDA). Furthermore, a positive correlation between EDA and human-likeness appraisal reaction time upholds one of the most common explanations of the UV – the categorization ambiguity. The absence of the significant relationship between declared comfort and EDA advocates the necessity of physiological measures for UV studies.

This paper presents a pre-validated set of 12 static 3D stimuli for the needs of uncanny valley-related studies. We provide the set along with guidelines on how to use it, which are based on the aggregated data analysis covering previous laboratory and online studies. Guidelines cover the models’ characteristics (in terms of human-likeness and other visual traits), issues related to the stimuli presentation and study groups. As the set is publicly available, we believe that it enhances future studies aimed at replicating the uncanny valley effect.