People make trait inferences based on facial appearance despite little evidence that these inferences accurately reflect personality. The authors tested the hypothesis that these inferences are driven in part by structural resemblance to emotional expressions. The authors first had participants judge emotionally neutral faces on a set of trait dimensions. The authors then submitted the face images to a Bayesian network classifier trained to detect emotional expressions. By using a classifier, the authors can show that neutral faces perceived to possess various personality traits contain objective resemblance to emotional expression. In general, neutral faces that are perceived to have positive valence resemble happiness, faces that are perceived to have negative valence resemble disgust and fear, and faces that are perceived to be threatening resemble anger. These results support the idea that trait inferences are in part the result of an overgeneralization of emotion recognition systems. Under this hypothesis, emotion recognition systems, which typically extract accurate information about a person's emotional state, are engaged during the perception of neutral faces that bear subtle resemblance to emotional expressions. These emotions could then be misattributed as traits.
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