Abstract
Which facial characteristics do people rely on when forming personality impressions from faces? Previous research has uncovered an array of facial features that influence people’s impressions. Even though some (classes of) features, such as facial width-to-height ratio or resemblances to emotional expressions, play a central role in theories of social perception, their relative importance in impression formation remains unclear. Here, we model faces along a wide range of theoretically important dimensions. We use machine learning to test how well 31 features predict impressions of trustworthiness and dominance in a diverse set of 597 faces. In line with overgeneralization theory, emotion resemblances were most predictive of both traits. Other features that have received a lot of attention in the literature, such as facial width-to-height ratio, were relatively uninformative. Our results highlight the importance of modeling faces along a wide range of dimensions to elucidate their relative importance in impression formation.
Original language | English |
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Publication status | Published - 2020 |