How Facial Expressions Can Predict Ad Sharing

How Facial Expressions Can Predict Ad Sharing

  • Daniel McDuff, Microsoft Research; Jonah Berger, Wharton School of the University of Pennsylvania -- JOURNAL OF ADVERTISING RESEARCH
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Summary

Companies in a variety of industries are working to harness the power of social sharing, both online and offline. The challenge is getting people to share, and understanding what makes them do so. So, what can advertisers do to design ads that are more likely to be shared? The answer, according to research published in the latest issue of the Journal of Advertising Research, lies in data from facial coding. To understand why some ads get shared more than others, these authors examined the link between people’s facial expressions and sharing, using artificial intelligence methodology. “Facial analysis provides an unobtrusive way of measuring emotional reactions that can be performed quickly, easily and cheaply at scale,” they noted. This opens up possibilities for further research as well as suggestions for boosting shares.

Daniel McDuff (damcduff@microsoft.com) is a principal researcher at Microsoft, where he is working on scalable artificial intelligence tools for understanding human behavior, health and well-being. Previously, he was director of research at Media Lab spinout Affectiva, where he led analysis of the largest facial expression dataset in the world.

Jonah Berger (jberger@wharton.upenn.edu) is a marketing professor at the Wharton School of the University of Pennsylvania. He is an expert on word of mouth, natural-language processing and how products, ideas and behaviors catch on. Berger has authored 50 articles in peer-reviewed journals, and books including Simon and Schuster’s Contagious (2013), Invisible Influence (2016), and The Catalyst: How to Change Anyone’s Mind (2020).