What Makes Online Content Viral?
By Jonah A. Berger, Katherine L. Milkman. 2012
3,056 citations recorded by the source corpus.
Subfields: Literature and Literary Theory, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/f4b52788278bdfea71c55dea1a82c41845a98fbb
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Literature and Literary Theory
- David A. Hirshleifer
- K. Swani
- Andrew T. Stephen
- George R. Milne
- Naveen Donthu
- Alixandra Barasch
- Brian P. Brown
- A. Assaf
In Sociology and Political Science
- Andrew T. Stephen
- Jonah A. Berger
- Naveen Donthu
- R. Fazio
- Stefan Stieglitz
- Grant Packard
- Jay J. Van Bavel
- K. Swani
Citations in the corpus
- Balancing on the Creative Highwire (2016, background): “…success of new ideas with consumers, future research could explore creative forecasting with other audiences and outcomes, such as forecasting the staying power (Hargadon and Douglas, 2001), viral potential (Berger and Milkman, 2012), or cultural impact (Rao, Monin, and Durand, 2003) of new ideas.”
- What messages to post? Evaluating the popularity of social media communications in business versus consumer markets ☆ (2017, methodology): “Although “buying” fansmay increase popularity, this strategy's impact is limited if it fails to popularize brand page posts through increased likes and/or comments so that brand messages are shared throughout a viewer's network (Berger and Milkman, 2012).”
- Virality Prediction and Community Structure in Social Networks (2013, background): “Existing research has attempted to characterize viral memes in terms of message content [22], temporal variation [16, 24], influential users [19, 28], finite user attention [18, 21], and local neighborhood structure [10].”
- Online Review Helpfulness: Role of Qualitative Factors (2016, background): “Thus, sentimental tone of the review can influence the way information is processed (Berger and Milkman, 2012; Hu et. al, 2014).”
- Using Message Strategy to Drive Consumer Behavioral Engagement on Social Media (2018, background): “The findings also add to earlier empirical work, which emphasized on emotional cues as an essential precursor to content transmission in online environments (Berger and Milkman, 2012; Yuki, 2015).”
- News Sharing in Social Media: A Review of Current Research on News Sharing Users, Content, and Networks (2015, background): “Not surprisingly, the ranking or placing of an article on a given website affects its sharing probability (Berger & Milkman, 2012): Articles that are placed more prominently have a higher chance to be shared.”
- The Emotions that Drive Viral Video (2013, background): “For instance, where Berger and Milkman (2012) reported high and low levels of amusement, we chose instead to use hilarity as the high arousal variant of the primary emotion of humor and amusement as the low arousal variant.”
- Detecting, Preventing, and Mitigating Online Firestorms in Brand Communities (2019, background): “Berger and Milkman (2012) show that New York Times newspaper stories that include more intensive high-arousal emotions (e.g., fear/anxiety, anger) prompt emailed shares to others more frequently than stories with more intensive low-arousal emotions (e.g., sadness).”