We are less free than how we think: Regular patterns in nonverbal communication."

In Alessandro Vinciarelli, Anna Esposito, Mohammad Tayarani, Giorgio Roffo, Filomena Scibelli, Perrone Francesco & Dong BachVo, Multimodal Behavior Analysis in the Wild Advances and Challenges Computer Vision and Pattern Recognition. pp. Pages 269-288 (2019)
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Abstract

The goal of this chapter is to show that human behavior is not random but follows principles and laws that result into regular patterns that can be not only observed, but also automatically detected and analyzed. The word “behavior” accounts here for nonverbal behavioral cues (e.g., facial expressions, laughter, gestures, etc.) that people display, typically outside conscious awareness, during social interactions. In particular, the chapter shows that observable behavioral patterns typically account for social and psychological differences that cannot be observed directly. Therefore, the analysis of behavioral patterns is important from a human sciences point of view because it helps to understand how people work. Furthermore, it is becoming increasingly important from a technological point of view because observable behavior can be thought of as the physical, machine detectable trace of social and psychological phenomena. In particular, if it is possible to automatically detect and interpret behavioral patterns, it means that machines can make sense of social and psychological phenomena in the same way as people do.

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Author Profiles

Anna Esposito
Università degli Studi di Roma "La Sapienza"
Francesco Perrone
University of Glasgow

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