AI Article Synopsis
- Inferring emotions is essential for social interactions, but traditional studies often oversimplify by only looking at static cues like facial expressions.
- The Emotion Segmentation Paradigm was used in three studies with over 500 participants to analyze how people notice changes in emotions during continuous narratives, indicating a more complex understanding of emotions.
- Results showed consistent individual differences in how well people segmented emotions, and a correlation between a person's knowledge of emotion vocabulary and their ability to correctly infer emotional changes.
Article Abstract
Inferring emotion is a critical skill that supports social functioning. Emotion inferences are typically studied in simplistic paradigms by asking people to categorize isolated and static cues like frowning faces. Yet emotions are complex events that unfold over time. Here, across three samples (Study 1 N = 222; Study 2 N = 261; Study 3 N = 101), we present the Emotion Segmentation Paradigm to examine inferences about complex emotional events by extending cognitive paradigms examining event perception. Participants were asked to indicate when there were changes in the emotions of target individuals within continuous streams of activity in narrative film (Study 1) and documentary clips (Study 2, preregistered, and Study 3 test-retest sample). This Emotion Segmentation Paradigm revealed robust and reliable individual differences across multiple metrics. We also tested the constructionist prediction that emotion labels constrain emotion inference, which is traditionally studied by introducing emotion labels. We demonstrate that individual differences in active emotion vocabulary (i.e., readily accessible emotion words) correlate with emotion segmentation performance.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11332234 | PMC |
| http://dx.doi.org/10.1038/s44271-023-00039-4 | DOI Listing |
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