AUTHOR=Tsankova Elena , Tair Ergyul TITLE=Meta-Accuracy on the Internet: Initial Tests of Underlying Dimensions, Contributing Factors, and Biases JOURNAL=Frontiers in Psychology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.837931 DOI=10.3389/fpsyg.2022.837931 ISSN=1664-1078 ABSTRACT=

Meta-accuracy (correspondence between how we think others perceive us and how they really perceive us) of first impressions on the Internet has the potential to shape subsequent interactions. Aiming to enhance understanding of the underlying perceptual dimensions, the contribution of social competence, and the existence of positive/negative bias in first impressions’ meta-accuracy online, we conducted a study in a simulated asynchronous social-media-type setting. Target participants uploaded a selfie, wrote a short description of themselves, provided estimates of how warm and competent they believed others would find them based on their selfies and texts (metaperception), and completed two social competence questionnaires (general and Internet-specific). Perceiver participants assessed the warmth and competence of the selfies and texts as well (others’ perception). Meta-accuracy was measured as the absolute difference between metaperception and others’ perception. Through correlational analyses, we confirmed that meta-accuracy of first impressions on the Internet aligned with the universal dimensions of social cognition (warmth and competence), found sporadic evidence for the positive association between meta-accuracy and social competence, and showed that meta-accuracy for specific Internet expressive means varied with varying proficiency in these means. Through t-tests, we demonstrated positive meta-accuracy bias for selfies along the warmth dimension and negative bias for text along the competence dimension. Overall, our results suggest the primacy of warmth and uniqueness of the male targets-female perceivers combination for meta-accuracy on the Internet. Our findings expand knowledge about first impressions’ meta-accuracy on the Internet.