Sixteen facial expressions occur in similar contexts worldwide.
Level 3 - non-randomized controlled study
Large-scale observational cross-sectional study using automated machine-learning analysis of naturalistic video data.
PubMed 33328631 · doi:10.1038/s41586-020-3037-7
What was done
Deep neural networks were applied to 6 million naturalistic videos sourced from 144 countries across 12 world regions. The researchers conducted two experiments to measure whether 16 predefined categories of facial expressions systematically co-occurred with thousands of real-world social contexts (such as weddings or sporting competitions).
What was found
Each of the 16 facial expression categories showed distinct associations with specific social contexts. These context-expression associations were 70% preserved across 12 world regions. Differences in the frequency of specific facial expressions across regions varied as a function of which contexts were most salient.
Why it matters
Demonstrates that dynamic facial expressions have systematic, predictable associations with specific social situations globally, providing large-scale real-world data supporting cross-cultural commonalities in human expressive behavior.
Limits
The abstract does not report the number of unique human participants across the 6 million videos. Analysis relies entirely on automated deep neural network inference of expressions and contexts rather than direct measurement of internal emotional states. Internet-sourced video data may carry substantial demographic, cultural, and upload-selection biases.