Understanding Mood of the Crowd with Facial Expressions: Majority Judgment for Evaluation of Statistical Summary Perception

Abstract

We intuitively perceive mood or collective information of facial expressions without much effort. Although it is known that statistical summarization occurs even for faces instantaneously, it might be hard to perceive precise summary statistics of facial expressions (i.e., using all of them equally) since recognition of them requires the binding of multiple features of a face. This study assessed which information is extracted from the crowd to understand mood. In a series of experiments, twelve individual faces with happy and neutral expressions (or angry and neutral expressions) were presented simultaneously, and participants reported which expression appeared more frequently. To perform this task correctly, participants must perceive precise distribution of facial expressions in the crowd. If participants could perceive ensembles based on every face instantaneously, expressions presented on more than half of the faces (in a single ensemble/trial) would have been identified as more frequently presented and the just noticeable difference would be small. The results showed that participants did not always report seeing emotional faces more frequently until much more emotional than neutral faces appeared, suggesting that facial expression ensembles were not perceived from all faces. Manipulating the presentation layout revealed that participants’ judgments highly weight only a part of the faces in the center of the crowd regardless of their visual size. Moreover, individual differences in the precision of summary statistical perception were related to visual working memory. Based on these results, this study provides a speculative explanation of summary perception of real distinctive faces.