Within-Person Variability in Social Evaluation

When meeting someone for the first time, we not only extract a wealth of information about their age, gender, ethnicity, or mood, but we also evaluate them on social dimensions such as attractiveness, trustworthiness, or dominance. What makes these social inferences important and interesting is the fact that people agree with each other’s evaluations and that they can influence our attitudes and behaviours, even if evidence for their accuracy is only limited. Existing face evaluation models focus on the identity level, arguing that a person is either, say, trustworthy or untrustworthy, regardless of the many different ways they might look. Recent evidence, however, suggests that images of the same person can vary just as much as images of different people, i.e. people rather have trustworthy- or untrustworthy-looking images of themselves. Here, I explore the spread and magnitude of such within-person variability in social evaluation. This is accomplished by sampling natural face variability and using images with different pose, emotional expression, lighting, etc. that are representative of real life social interactions. In addition to idiosyncratic variability, experiments described here aim to examine social evaluation across gender and familiarity as well as investigate the implications of trait inferences for face recognition. I then address social evaluation across modality, integrating visual information from the face and acoustic information from the voice. My findings show comparable within- and between-person variability in social ratings and demonstrate that idiosyncratic variability alone can bring about significant changes in trait attribution. This suggests that social evaluation depends on both identity and image properties. Finally, I demonstrate the automaticity of audiovisual integration in social evaluation and show that the relative contribution of face and voice cues is different for the two fundamental social dimensions. Ultimately, this brings us a step closer to understanding integrated person perception