Titel
Happiness is easy to find - People recognize happy faces better than angry faces
AutorInnen
Kloss, A., Pratz, V., Lenze, E., Patricny, J., Götzfried, M.
Abstract
Background: Face perception is ubiquitous in the life of every human. The identification of emotional expressions is key to judging other peoples intentions, predicting behavior and handling social interactions. One question regarding this identification is whether happy or angry faces are detected more efficiently. The existing literature is inconclusive. Method: Using the recently introduced Mood of the Crowd (MoC) paradigm (Bucher & Voss, 2019), we assess the question whether angry or happy faces can be more efficiently distinguished from neutral faces in a crowd setting. We gathered a convenience sample of 32 participants (after exclusion). Randomly composed groups of 20 faces from the KDEF database were judged regarding their overall valence. Differences in mean reaction times and accuracy were assessed using a 2x4-repeated measures ANOVA. A diffusion model was used to separate the efficiency of the stimulus accumulation from other factors like response behavior or biases in responses. Results: Due to violation of the distributional assumptions, the results of the ANOVA cannot be interpreted. In line with our hypothesis, we find higher drift rates (i.e., easier detection) of happy vs. neutral faces compared to angry vs. neutral faces. We find that a larger discrepancy in the number of neutral vs. emotional faces (5 and 15 vs. 7 and 13) leads to increased drift-rates (i.e., easier detection) . Discussion: Our results align with the happiness superiority effect. The differences can be most likely explained by the saliency that happy faces have due to smiling with teeth.
Schlagworte
diffusion model, emotion recognition effect, happiness superiority effect, mood of the crowd