Clickbait and Virality Are Creating a New Science of Internet Trends
Clickbait is brilliant. Clickbait is annoying. Clickbait is the future. Clickbait must die.
Whatever your opinion on the ubiquity of BuzzFeed-esque headlines or the recent influx of made-to-go-viral content, you have to admit that there’s something fascinating about clickbait. It’s certainly caught the eyes of the folks over at MIT Technology Review, where a post went up this week detailing the fledgling science of virality. The question at the heart of this emerging study:
“What is the difference between stories that become viral and those that don’t?”
The article explores one possible answer: emotional response. Focus is placed on the work of two researchers — Marco Guerini at Trento Rise in Italy and Jacopo Staiano at Sorbonne Université in Paris — who are working to examine the psychology behind viral content, specifically which emotions ought content-creators appeal to in order to earn the most exposure:
“Psychologists have long categorized emotion using a three-dimensional scale known as the Valence-Arousal-Dominance model. The idea is that each emotion has a valence, whether positive or negative and a level of arousal, which is high for emotions such as anger and low for emotions like sadness. … Guerini and Staiano say that posts generate more comments when they are associated with emotions of high arousal, such as happiness and anger, and with emotions where people feel less in control, such as fear and sadness.
By contrast, posts generate more social votes when associated with emotions people feel more in control of, such as inspiration.”
Guerini and Staiano represent but a small portion of the greater scientific community developing methods for analyzing virality. Their research has practical applications with regard to internet marketing. It’s also somewhat captivating to explore the inner machinations of emerging trends playing out right in front of our eyes.
Below, Big Think expert Scott Galloway explains the process through which viral content spreads:
Read more at MIT Technology Review.
Photo credit: View Apart / Shutterstock
