Voters evaluate politicians not just by what they say, but also how they say it, via facial displays of emotions and vocal pitch. Candidate characteristics can shape how leaders use – and how voters react to – nonverbal cues. Drawing on role congruity expectations, we focus on how gender shapes the use of and reactions to facial, voice, and textual communication in political debates. Using full-length debate videos from four German national elections (2005–2017) and a minor debate in 2017, we employ computer vision, machine learning, and text analysis to extract facial displays of emotion, vocal pitch, and speech sentiment. Consistent with our expectations, Angela Merkel expresses less anger and is less emotive than her male opponents. We combine second-by-second candidate emotions data with continuous responses recorded by live audiences. We ﬁnd that voters punish Merkel for anger displays and reward her happiness and general emotional displays.
Categories: Gender, Politics