Amplification in the evaluation of multiple emotional expressions over time

Amit Goldenberg (), Jonas Schöne, Zi Huang, Timothy D. Sweeny, Desmond C. Ong, Timothy F. Brady, Maria M. Robinson, David Levari, Jamil Zaki and James J. Gross
Additional contact information
Amit Goldenberg: Harvard University
Jonas Schöne: University of Oxford
Zi Huang: Harvard University
Timothy D. Sweeny: University of Denver
Desmond C. Ong: National University of Singapore
Timothy F. Brady: University of California
Maria M. Robinson: University of California
David Levari: Harvard University
Jamil Zaki: Stanford University
James J. Gross: Stanford University

Nature Human Behaviour, 2022, vol. 6, issue 10, 1408-1416

Abstract: Abstract Social interactions are dynamic and unfold over time. To make sense of social interactions, people must aggregate sequential information into summary, global evaluations. But how do people do this? Here, to address this question, we conducted nine studies (N = 1,583) using a diverse set of stimuli. Our focus was a central aspect of social interaction—namely, the evaluation of others’ emotional responses. The results suggest that when aggregating sequences of images and videos expressing varying degrees of emotion, perceivers overestimate the sequence’s average emotional intensity. This tendency for overestimation is driven by stronger memory of more emotional expressions. A computational model supports this account and shows that amplification cannot be explained only by nonlinear perception of individual exemplars. Our results demonstrate an amplification effect in the perception of sequential emotional information, which may have implications for the many types of social interactions that involve repeated emotion estimation.

Date: 2022
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DOI: 10.1038/s41562-022-01390-y

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