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

2019/04/24 by Gerard J. Tellis, Deborah J. MacInnis, Seshadri Tirunillai +1 · 480 citations
Arts and Humanities · Business, Management and Accounting · Mathematics · Psychology · Social Sciences · #Advertising #Affect (linguistics) #Amusement #Business #Communication #Computer science #Consumer Behavior in Brand Consumption and Identification #Content (measure theory) #Digital Marketing and Social Media #Emotional contagion #Mathematics #Media Influence and Health #Microblogging #Psychology #Social media #Social psychology #Surprise #Test (biology) #World Wide Web

paper · doi:10.1177/0022242919841034

published in Journal of Marketing 83(4), 1-20 (SAGE Publishing)

openalex publication_date 2019/04/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

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.

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