Date of Award

Spring 1-1-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Psychology

First Advisor

Gendron, Maria

Abstract

Our understanding of what others around us feel, a process referred to as emotion inference, fundamentally shapes our behavior and social interactions. Early work largely focused on how people infer emotions from isolated, static, canonical facial expressions. Accumulating evidence and theoretical advancements suggest that emotion inference, instead, is a complex process that involves making meaning about a target’s experience by dynamically synthesizing information from multiple sources with existing knowledge. Yet, a comprehensive empirical account that captures this complexity is largely missing from the literature. In this dissertation, I propose and systematically test a research framework that addresses this complexity of emotion inference. Across three empirical chapters, I examine how people integrate face and situation cues, represent them in everyday life, and attend to them unfolding dynamically, to infer others’ emotions. I demonstrate that in both static and dynamic instances people largely use information about situations, by integrating it with faces or exclusively relying on it, to infer emotions. In addition to these group-level patterns, I show that people vary in the degree to which they use situational information, that this variation is stable, predicted by emotion knowledge, and has consequences for how precisely individuals infer emotions and represent the underlying psychological features of situations leading to emotions. Together, this work advances our understanding of how people build rich models of others’ emotional lives and illustrates that the complexity of emotion inference has consequences for social lives.

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