Skip to Content Skip to Footer
What Drives Virality (Sharing) of Online Digital Content? The Critical Role of Information, Emotion, and Brand Prominence

What Drives Virality (Sharing) of Online Digital Content? The Critical Role of Information, Emotion, and Brand Prominence

Gerard J. Tellis, Deborah J. MacInnis, Seshadri Tirunillai and Yanwei Zhang

JM Insights in the Classroom

Teaching Insights

Based on a JM study, this presentation summarizes six critical drivers of shares and virality of YouTube video ads.

Access Classroom Lecture Slides

Related Marketing Courses: ​
Digital Marketing, Marketing Communications, Social Media Marketing

Full Citation: ​
Tellis, Gerard J., Deborah J. MacInnis, Seshadri Tirunillai, and Yanwei Zhang (2019), “What Drives Virality (Sharing) of Online Digital Content? The Critical Role of Information, Emotion, and Brand Prominence,” Journal of Marketing, 83 (4), 1–20.

Article Abstract
The authors test five theoretically derived hypotheses about what drives video ad sharing across multiple social media platforms. Two independent field studies test these hypotheses using 11 emotions and over 60 ad characteristics. The results are consistent with theory and robust across studies. Information-focused content has a significantly negative effect on sharing, except in risky contexts. Positive emotions of amusement, excitement, inspiration, and warmth positively affect sharing. Various drama elements such as surprise, plot, and characters, including babies, animals, and celebrities arouse emotions. Prominent (early vs. late, long vs. short duration, persistent vs. pulsing) placement of brand names hurts sharing. Emotional ads are shared more on general platforms (Facebook, Google+, Twitter) than on LinkedIn, and the reverse holds for informational ads. Sharing is also greatest when ad length is moderate (1.2 to 1.7 minutes). Contrary to these findings, ads use information more than emotions, celebrities more than babies or animals, prominent brand placement, little surprise, and very short or very long ads. A third study shows that the identified drivers predict sharing accurately in an entirely independent sample.

Advertisement

Special thanks to Kelley Gullo and Holly Howe, Ph.D. candidates at Duke University, for their support in working with authors on submissions to this program.

Search other Insights in the Classroom​

Read a managerial summary of this paper

More from the Journal of Marketing​​​​​​​

Gerard J. Tellis is Professor, Director of the Center for Global Innovation, and Neely Chair of American Enterprise, Marshall School of Business, University of Southern California.

Deborah J. MacInnis is Charles L. and Ramona I. Hilliard Professor of Business Administration and Professor of Marketing, Marshall School of Business, University of Southern California, USA.

Seshadri Tirunillai is Assistant Professor of Marketing, University of Houston, USA.

Yanwei Zhang is Staff Data Scientist, Uber Technologies Inc.

The owner of this website has made a commitment to accessibility and inclusion, please report any problems that you encounter using the contact form on this website. This site uses the WP ADA Compliance Check plugin to enhance accessibility.