I expect you to be happy, so I see you smile: A multidimensional account of emotion attribution

Abstract

Constructivist theories of emotions and empirical studies have been increasingly stressing the role of contextual information and cultural conventions in emotion recognition. We propose a new account of emotion recognition and attribution that systematically integrates these aspects, and argue that emotion recognition is part of the general process of person impression formation. To describe the structural organization and the role of background information in emotion recognition and attribution, we introduce situation models and personal models. These models constitute the top-level structures in a complex hierarchy of dimensions which considers different types of basic emotion cues. Thus, we propose a multidimensional account of emotion recognition which enables us to integrate the top-down and bottom-up processes involved: basic emotion cues in certain contexts can trigger situation models and person models, which influence emotion recognition which, in turn, reinforce or modify these models. We argue that this kind of loop deeply affects the way emotions enter our social interactions. Our account is in line with the “normative turn” of social cognition, that stresses the way social expectations actively shape the patterns we recognize, and make, in our social world.