Research 2019-01-09T14:29:53+00:00
Using a dataset of over 90,000 Facebook posts from top brands, I examine how the emotions of love, shock, sadness, anger, and humor influence whether a piece of content goes viral. The answer is not universal. For instance, emotions that work best for for-profits do not work best for non-profits. I argue that the explanation can be traced to impression management.

THE PAPER: Schiro, Julie L. (2018), “What, How, and Why Emotions Go Viral,” Manuscript in Progress.

We outline best practices in digital marketing, from going viral to targeting, for social marketers eager to make an impact online. We focus on a notoriously non-digital domain – food safety communications – as a template for breaking into the digital space.

THE PAPER: Shan, Liran, Julie L. Schiro* Mimi Tatlow-Golden, Lucia De Luca, Liyen Julien Liu, Si Chen, Chenguang Li, and Patrick Wall (2018), “The Potential of Digital Marketing Technologies in Public Engagement with Food Safety and Healthy Eating Communication,” revising for invited revision at Trends in Food Science and Technology. *Equal Authorship

Instead of being scary or depressing, many social marketers are being funny.  Across two papers, we investigate whether humor can “sell” good behaviors as well as their scary and sad counterparts.

THE PAPERS: Schiro, Julie L. (2018), “Using Humor to ‘Sell’ Good Life Choices,” Manuscript in Progress.

McGraw, A. P., Julie L. Schiro, and Philip M. Fernbach (2015), “Not a Problem: A Downside of Humorous Appeals,” Journal of Marketing Behavior, 1 (2), 187-208. Download PDF

People are poor intuitive statisticians. We propose a reason. When people judge the correlation between two continuous variables, they mentally categorize it into a 2×2 contingency table: high X high Y, high X low Y, low X high Y, low X low Y. People pay more attention to some cells (high-high) than others (low-low), resulting in predictable interpretation errors. Specifically, people overweigh the importance of high-high evidence and underweigh the importance of low-low evidence. The result is that people judge datasets with identical correlations but different distributions of points differently. Visualizing data in scatterplots does not improve judgments. However, overlaying simple visual cues do. For instance, drawing a circle around the points of a scatterplot inhibits categorical thinking about the data, which improves people’s judgments by reducing their tendency to overweigh high-high evidence and underweigh low-low evidence.


de Langhe, Bart, Philip M. Fernbach, and Julie L. Schiro (2016), “Two-By-Two: Categorical Thinking in the Interpretation of Continuous Bivariate Data,” Manuscript in Preparation.