Abstract
Inference of social traits from faces is a prominent factor in everyday social interactions. As such it is supposed to be susceptible to evolutionary pressures affecting detection sensitivities of specific social context. Previous studies have shown in a multi trait rating task (Oosterhof & Todorov, 2008), that the valence dimension (first principal component) has been found to capture most of the variance (68%) whereas the second principle component, well aligned with dominance, was found to capture only 18% of the variance. It has been suggested that the latter structure expresses the priority of evaluation of intention over evaluation of dominance in a chance encounter. Here we address the issue of the modulation of social impression from faces across varying viewing distance. In a four social trait rating task (trustworthiness, dominance, attractiveness and aggressiveness) and simulation of varying viewing distances ranging from 2.5 to 80m we addressed this question by (i) evaluating the composition of diagnostic information across that viewing distance by classification images (ii) reconstructing the structure of the viewing-distance-dependent social space by measuring its principal components. The results show a varying composition of diagnostic information across viewing distance. Whilst in long viewing distance face and hair color (e.g. face redness) serve as major diagnostic features, in short viewing distance inner facial features (such as eyebrows) become diagnostic as well. In addition we show that at a long viewing distance loading on the first principal component of dominance is high and that of trustworthiness is low. When viewing distance is becoming shorter the loading on the first principal component of dominance becomes lower and that of trustworthiness becomes higher. The latter results suggest a viewing distance dependent tuning of social perception: priority of evaluation of counterpart's capacity in far viewing distance and priority of intentions in short distance.
Meeting abstract presented at VSS 2014