At a time when nativism is on the rise, research is revealing the universality of human emotional expression.
Whether it’s a birthday party in Brazil, a funeral in Kenya or protests in Hong Kong, people all use variations of the same facial expressions in similar social contexts, such as smiles, frowns, grimaces and frowns, a new study from UC finds Berkeley.
The findings, published today, December 16, 2020, in the journal Nature, affirm the universality of human emotional expression across geographic and cultural boundaries at a time when nativism and populism are on the rise around the world.
“This study shows how remarkably similar people in different corners of the world are in the way we express emotions in light of the most meaningful contexts of our lives,” said study co-lead author Dacher Keltner, a professor of psychology at UC Berkeley. founder and director. of the Greater Good Science Center.
Researchers from UC Berkeley and Google used machine learning technology known as a “ deep neural network ” to analyze facial expressions in approximately 6 million video clips uploaded to YouTube from people in 144 countries in North, Central and South America , Africa, Europe, the United States. Middle East and Asia.
“This is the first global analysis of how facial expressions are used in everyday life, and it shows us that universal human emotional expressions are much richer and more complex than many scientists previously thought,” said lead author Alan Cowen, a researcher at both UC Berkeley. like Google, who helped develop the deep neural network algorithm and led the research.
Cowen has created an online interactive map that shows how the algorithm tracks variations of facial expressions related to 16 emotions.
In addition to promoting cross-cultural empathy, potential uses include helping people who have difficulty reading emotions, such as children and adults with autism, to recognize the faces people usually make to convey certain feelings.
The typical human face has 43 different muscles that can be activated around the eyes, nose, mouth, jaw, chin and forehead to create thousands of different expressions.
How they conducted the research
First, researchers used Cowen’s machine learning algorithm to capture facial expressions shown in 6 million video clips of events and interactions worldwide, such as watching fireworks, dancing joyfully, or comforting a sobbing child.
They used the algorithm to track 16 facial expressions commonly associated with entertainment, anger, awe, concentration, confusion, contempt, contentment, desire, disappointment, doubt, elation, interest, pain, sadness, surprise, and triumph.
They then correlated the facial expressions with the contexts and scenarios in which they were created in different world regions and found remarkable similarities in the way people use facial expressions across geographic and cultural boundaries in different social contexts.
“We found that rich nuances in facial behavior – including subtle expressions that we associate with awe, pain, triumph, and 13 other feelings – are used in similar social situations around the world,” Cowen said.
For example, Cowen noted that in the video clips, people all over the world tended to gaze in awe at fireworks displays, show satisfaction at weddings, frown in concentration when performing martial arts, show doubt at protests, pain at lifting weights and triumphing at rock concerts and competitive sporting events.
The results showed that people from different cultures share about 70% of the facial expressions used in response to different social and emotional situations.
“This supports Darwin’s theory that the expression of emotions in our faces is universal among humans,” said Keltner. “The physical representation of our emotions can define who we are as a species, improving our communication and collaboration skills and ensuring our survival.”
Reference: “Sixteen Facial Expressions Occur in Similar Contexts Worldwide” by Alan S. Cowen, Dacher Keltner, Florian Schroff, Brendan Jou, Hartwig Adam and Gautam Prasad, December 16, 2020, Nature.
DOI: 10.1038 / s41586-020-3037-7
In addition to Keltner and Cowen, the study’s co-authors are Florian Schroff, Brendan Jou, Hartwig Adam, and Gautam Prasad, all at Google.