4.5 Article

Reading People's Minds From Emotion Expressions in Interdependent Decision Making

Journal

JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY
Volume 106, Issue 1, Pages 73-88

Publisher

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/a0034251

Keywords

emotion expressions; appraisal theories; reverse appraisal; decision making; theory of mind

Funding

  1. Div Of Information & Intelligent Systems
  2. Direct For Computer & Info Scie & Enginr [1211064] Funding Source: National Science Foundation

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How do people make inferences about other people's minds from their emotion displays? The ability to infer others' beliefs, desires, and intentions from their facial expressions should be especially important in interdependent decision making when people make decisions from beliefs about the others' intention to cooperate. Five experiments tested the general proposition that people follow principles of appraisal when making inferences from emotion displays, in context. Experiment 1 revealed that the same emotion display produced opposite effects depending on context: When the other was competitive, a smile on the other's face evoked a more negative response than when the other was cooperative. Experiment 2 revealed that the essential information from emotion displays was derived from appraisals (e. g., Is the current state of affairs conducive to my goals? Who is to blame for it?); facial displays of emotion had the same impact on people's decision making as textual expressions of the corresponding appraisals. Experiments 3, 4, and 5 used multiple mediation analyses and a causal-chain design: Results supported the proposition that beliefs about others' appraisals mediate the effects of emotion displays on expectations about others' intentions. We suggest a model based on appraisal theories of emotion that posits an inferential mechanism whereby people retrieve, from emotion expressions, information about others' appraisals, which then lead to inferences about others' mental states. This work has implications for the design of algorithms that drive agent behavior in human-agent strategic interaction, an emerging domain at the interface of computer science and social psychology.

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