At a time when nativism is on the rise, a study reveals the universality of human emotional emotion.
Whether at a birthday party in Brazil, a funeral in Kenya or protests in Hong Kong, everyone uses variations of the same facial expressions in similar social contexts, such as smiles, frowns, grimaces and scowls, a new UC Berkeley study shows.
The findings, published today, December 16, 2020, are in the journal Nature, the universal affirmation of human emotional sentiment across geographical and cultural boundaries at a time when naturalism and republicanism are on the rise across the globe.
“This study shows how amazing people in different parts of the world are in terms of how we express feelings against the most meaningful contexts of our lives,” said the co-lead author. study Dacher Keltner, UC Berkeley professor of psychology and founding director of the Great Math Science Center.
Researchers at UC Berkeley and Google used machine learning technology called “deep neural network” to analyze facial expressions in approximately 6 million video clips uploaded to YouTube from people in 144 countries spanning North, Central and South America, Africa, Europe. Middle East and Asia.
“This is the first worldwide study of the use of facial expressions in everyday life, and shows us that all human emotional expressions are richer and more complex than many used. -science previously embraced it, ”said study lead author Alan Cowen, a researcher at both UC Berkeley and Google who helped develop a deep neural network algorithm and led the study.
Cowen created an online interactive map that shows how the algorithm tracks changes in facial expressions related to 16 emotions.
In addition to encouraging cross-cultural empathy, potential applications include helping people who have difficulty reading emotions, such as children and children. adults with autism, recognizing the faces that people usually make to express certain feelings.
The normal human face has 43 different muscles that can be activated around the eyes, nose, mouth, jaws, chin, and brow to make thousands of different expressions.
How they did the study
Researchers first used Cowen’s machine learning algorithm to record facial expressions that appeared in 6 million video clips of events and interactions around the world, such as watching fireworks, dancing with joy, or consoling a sobbing child.
They used the algorithm to track examples of 16 facial expressions that one tends to be associated with fun, anger, surprise, concentration, upset, contempt, happiness, desire, disappointment, doubt, shouting, interest, pain, sadness, surprise, and victory.
Next, they linked the face expressions with the contexts and situations in which they were made across different parts of the world and found similarities in how people over geographical and cultural boundaries using facial expressions in different social contexts.
“We found that rich nuances in facial expressions – including subtle phrases that we associate with surprise, pain, impact, and 13 other emotions – are used in similar social situations on all over the world, ”said Cowen.
For example, Cowen noted that in the video clips, people all over the world tended to stare at fireworks displays, express joy at weddings, waking their breasts in focus when performing martial arts, show skepticism at protests, pain when lifting weights, and influence 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 expressing emotion in our faces is universal among humans,” Keltner said. “The physical expression of our emotions may define who we are as a gender, enhance our communication and co-operation skills and ensure our survival.”
Fact: “Sixteen face expressions appear in similar contexts around the world” by Alan S. Cowen, Dacher Keltner, Florian Schroff, Brendan Jou, Hartwig Adam and Gautam Prasad, 16 December 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, Adam Hartwig, and Gautam Prasad, all at Google.