Inter-subject correlation of audience facial expressions predicts audience engagement during theatrical performances

Abstract

Summary: During performances, audiences experience various emotional states, and these are reflected in their ongoing facial expressions. We investigated if audience engagement could be determined by measuring the inter-subject correlation (ISC) of non-invasively recorded audience facial expressions. We filmed the faces of multiple audience members at theatrical performances and determined the intensity of their different facial expressions throughout the performances. Neutral, happy, anger, and disgust expression ISCs accounted for up to 24% of the performance dramaturge’s predictions of audience engagement. Expression synchrony was greater between individuals in close proximity, suggesting effects of emotional contagion or cognitive similarities between neighboring individuals, whereas expression synchrony was greatest between individuals who were younger, female, and with greater levels of empathy, showing that individual characteristics impact shared audience experiences. Together, our results show that facial expression synchronization could be used as a real-time non-invasive indicator of engagement in audiences larger than achieved using previous approaches.

Keywords

• Artificial intelligence
• Psychology
• Social sciences