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72. Identifying Liars Through Automatic Decoding Of Children’S Facial Expressions., Kaila C. Bruer, Sarah Zanette, Xiaopan Ding, Thomas D. Lyon, Kang Lee
72. Identifying Liars Through Automatic Decoding Of Children’S Facial Expressions., Kaila C. Bruer, Sarah Zanette, Xiaopan Ding, Thomas D. Lyon, Kang Lee
Thomas D. Lyon
This study explored whether children’s (N=158; 4-9 years-old) nonverbal facial expressions can be used to identify when children are being deceptive. Using a computer vision program to automatically decode children’s facial expressions according to the Facial Action Coding System, this study employed machine learning to determine whether facial expressions can be used to discriminate between children who concealed breaking a toy(liars) and those who did not break a toy(nonliars). Results found that, regardless of age or history of maltreatment, children’s facial expressions could accurately (73%) distinguished between liars and nonliars. Two emotions, surprise and fear, were more strongly expressed by …