Reward, Affiliative, and Dominance Smiles are Categorized More Accurately when Defined in Morphological than Socio-Functional Terms

Little is known about the role that perceivers’ conceptual knowledge of the social and morphological aspects of facial expressions plays in emotion recognition. Here, we examine how smile conceptualization and dynamics impact the categorization of reward, affiliative, and dominance smiles based on the Simulation of Smiles Model. In Study 1 (n = 192), Polish participants read definitions of smiles formulated in either morphological or socio-functional terms. Next, they viewed dynamic or static expressions of these smiles and rated the extent to which each expression portrayed a reward, affiliative, and dominance smile. As predicted and consistent with previous studies, affiliative smiles were categorized more accurately when presented in dynamic than in static form. However, contrary to our expectations, the categorization was more accurate when smiles were defined in morphological than socio-functional terms. Studies 2 (n = 196) and 3 (n = 265) replicated the advantage of morphological over socio-functional conceptualizations in UK-based samples but did not unambiguously support the role of dynamics in smile categorization. Together, our findings suggest that the impact of expression dynamics on smile categorization may be more complex than previously assumed and point to the role of smile conceptualization in this process. Keywords: smile, facial expression, emotion categorization, facial dynamics, positive emotion