Spontaneous Content of Impressions of Naturalistic Face Photographs

Abstract

Social impressions from faces have been studied in psychology for over 100 years. These impressions are rapid, efficient, and consequential. Yet, disagreements about the content of face impressions remain. Across two studies (N = 4,526), we develop a taxonomy of spontaneous face impressions content by applying novel interdisciplinary methods from Artificial Intelligence text analysis to thousands of free-response descriptions of computer-generated faces. We identify a taxonomy of face impression dimensions, and describe their coverage, prevalence, directionality, and correlational structure. We characterize a diverse and nuanced taxonomy of content that, when compared to just the content that dominant low-dimensional models focus on, increases the coverage of spontaneous responses from about 50% to almost 100%. Our results describe general patterns of prevalence, indicating that dimensions from low-dimensional models (e.g., Sociability, Morality, Assertiveness) are highly prevalent, but that alternative dimensions such as Uniqueness and Health, among others, are also significantly prevalent in face impressions of naturalistic face photographs. Most dimensions show a positivity bias, and the correlational structure of the dimensions further supports the clustering of low-dimensional model’s content as separate from the expanded taxonomy dimensions. Finally, this expanded taxonomy improves predictions of general evaluations and decision making in various real-world relevant contexts. The derived taxonomy of spontaneous face impressions content is a foundation for further theoretical development and practical applications in an area central to human behavior.