Many FACETS, One Emotion: Reporting the Valence and Labeling of Emotional Faces

Document Type

Conference Proceeding

Publication Date

4-2025

Abstract

Common facial expressions correspond with universal emotions across cultures. Therefore, researchers need normative data from existing facial databases to study distinct processes that involve facial emotion recognition and facial identity recognition. FACETS (Faces Across Camera, Environment, Time, and Settings) is the most comprehensive option, including diversity, variability, and emotionality for 265 different facial image sets. Approximately N =300 participants will view several emotional facial images from the FACETS database and provide an emotional label (happiness, sadness, fear, anger, surprise, distinctiveness, or neutral), rate emotional valence (i.e., strength of emotion), and rate emotional genuineness (i.e., the degree to which the expression is a natural emotional response and not posed). We will calculate and report descriptive statistics for all 1590 FACETS images. By adding emotion ratings to the FACETS database, we aim to provide stimuli that support researchers’ future studies on topics such as emotional intelligence, mood disorders, and emotional development.

Comments

1:00-2:00 p.m.

BLH 266

Studies in Living and Learning

Amy Bohman, Moderator

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