We once again have new evidence of the universality of facial expressions (and emotions), but this time from a new approach. A new study examined the occurrence of 16 expressions in 6 million videos from 144 countries using machine learning .
Potential applications of this study include helping people who have trouble reading emotions, such as children and adults with autism, to recognize the faces humans make to convey certain feelings.
Neural networks
At least since the time of Aristotle, scholars have tried to understand how and why the face reveals our feelings, from joy to sadness. The universality debate is critical to understanding the nature, causes, and functions of emotions .
In the study, in two experiments using deep neural networks, the extent to which 16 types of facial expression were consistently produced in thousands of contexts in 6 million videos from 144 countries was examined.
In each region, certain facial configurations were observed with relative greater frequency in certain contexts . The associations were subtle (that is, the magnitude of the associations between facial expression and context tended to be weak), but surprisingly, the pattern of expression-context association observed in the videos from one region of the world was similar to those observed. from other regions of the world.
For example, in the various regions sampled, people in the videos performed facial-muscle movements labeled ‘awe’ more frequently in contexts involving fireworks, a parent, toys, a pet, and dancing than in contexts that did not include these. elements. such as those related to music, art, police, and team sports.
It was thus discovered that each type of facial expression had different associations with a set of contexts that were preserved by 70% in 12 regions of the world.
16 facial expressions that one tends to associate with amusement, anger, amazement, concentration, confusion, contempt, satisfaction, desire, disappointment, doubt, elation, interest, pain, sadness, surprise and triumph.
Consistent with these associations, the regions varied in the frequency with which different facial expressions occurred based on which contexts were most prominent . The results reveal fine patterns in human facial expressions that are preserved throughout the modern world.