@ARTICLE{Gablíková_Mária_Sex_2021,
 author={Gablíková, Mária and Halamová, Júlia},
 volume={vol. 52},
 number={No 1},
 journal={Polish Psychological Bulletin},
 pages={83-96},
 howpublished={online},
 year={2021},
 publisher={Committee for Psychological Science PAS},
 abstract={Our aim was to test existing sex and age stereotypes related to emotional expressivity, gender and age. This was a complex analysis of facial expressions of all basic emotions (anger, disgust, fear, happiness, sadness, and surprise) to everyday life stimuli observing a large sample (2,969 unique participants creating 39,694 recordings) using an Emotion Artificial Intelligence. Our data partially support emotion-specific stereotype that women express more affiliate emotions and men express more dominant emotions except for sadness. There were found correlations of emotion expression with age, however intensity and frequency of emotion expression did not follow the same pattern. Not eliminating the differences between men and women in the baseline facial appearance resulted in men expressing dominant emotions (anger and disgust) more intensively, and women expressing more affiliative emotions (happiness, fear, and surprise). To sum up, facial appearance can be one of the origins of the existing gender stereotypic socialisation stereotype.},
 type={Article},
 title={Sex and age differences in facial emotions expressions measured by artificial intelligence},
 URL={http://journals.pan.pl/Content/120166/PDF/2021-01-PPB-07-Gablikova.pdf},
 doi={10.24425/ppb.2021.136819},
 keywords={facial expressions, artificial intelligence, advertisement, age, sex, stereotypes, facial appearance},
}