Politicians can increase the appeal of their speeches through nonverbal cues such as gestures and vocal emphasis. Understanding the factors that make political speech appealing is central to political science research, yet studying nonverbal cues during political speech is difficult due to their audiovisual nature. Pose estimation models—a class of computer vision models that locate and trace human body key points, such as hands, ellbows, and shoulders throughout videos—offer a valuable opportunity to computationally assess politicians’ body language in video recordings.
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