  People often share news and information with their social connections, but
why do some advertisements get shared more than others? A large-scale test
examines whether facial responses predict sharing. Facial expressions play a
key role in emotional expression. Using scalable automated facial coding
algorithms, we quantify the facial expressions of thousands of individuals in
response to hundreds of advertisements. Results suggest that not all emotions
expressed during viewing increase sharing, and that the relationship between
emotion and transmission is more complex than mere valence alone. Facial
actions linked to positive emotions (i.e., smiles) were associated with
increased sharing. But while some actions associated with negative emotion
(e.g., lip depressor, associated with sadness) were linked to decreased
sharing, others (i.e., nose wrinkles, associated with disgust) were linked to
increased sharing. The ability to quickly collect facial responses at scale in
peoples' natural environment has important implications for marketers and opens
up a range of avenues for further research.
