2014-04-23

Co.Labs

The Surprising Role Of Social Deviance In Viral News

A new study I completed at the Columbia University J-school says there is a strong relationship between the "social deviance" of the event or topic in a headline and the number of retweets it gets on Twitter.



Social media platforms like Twitter and Facebook drive about 26% of all traffic to online news stories according to the analytics provider Chartbeat—even more if you’re Upworthy or BuzzFeed, to the point that social referral traffic overshadows everything else.

The key to earning those referrals? Clickbait and "curiosity gap" headlines that hook users and draw them in. Publishers of course want more audience, more clicks, and more revenue. So it’s not uncommon to find instruction manuals emerging like, "A Scientific Guide to Writing Great Headlines on Twitter, Facebook, and Your Blog," with data-driven tips such as "use numbers" or "ask a question" to drive click-throughs and re-shares. Upworthy tests dozens of possible headlines before settling on the one that works best for engagement.

It’s clear that headlines are an important part of the equation for creating an audience around content—but they’re also just the entry point. The underlying characteristics of the content also determine whether a story goes "viral."

For instance, news that evokes emotions (particularly positive ones, like awe, but also negative ones like anger and anxiety) are much more likely to be shared.

The Viral Multiplier: Social Deviance

Social deviance is another underlying characteristic that helps drive sharing of news on social media. It’s been known for some time that journalists are more likely to select socially deviant events for the news, creating a sort of warning mechanism about social threats to a community. But social deviance also appears to be a more general factor that can help explain interest, attention, and sharing of news on the ever-so-important social channels.

So what exactly is social deviance? When someone violates a social norm like plagiarism, or a legal norm like homicide, they’re committing an act of social deviance. Social norms are there to help define what is considered appropriate or inappropriate behavior in a given social situation. By learning about what is considered a norm violation it helps us understand the boundaries of our own behavior and what’s acceptable in our society or culture.

In a study I recently published at the Columbia University School of Journalism, my co-author and I analyzed 8,000 news headlines across eight major news outlets—and found that for six of the outlets there was a strong relationship between the social deviance of the event or topic behind the headline and the number of retweets it garnered on Twitter.

Given the two headlines: "Principal busted for spying on students through Facebook quits" and "Oil jumps to 9-month high after Iran cuts supply," which headline are you more likely to click on and share? Unless you’re a commodities trader, I would guess the first.

In the following chart you can see that the top 20% of tweets (sorted by number of retweets) had a larger proportion of socially deviant tweets than the bottom 20% of tweets. The upper echelon of the retweeted content contains more social deviance, 23.4%, than the bottom,14.6%.

With the exception of the Wall Street Journal and Chicago Tribune, the other outlets we studied showed that the top 20% of tweets tended to have a higher rate of social deviance than the bottom 20%.

Particularly tabloid publications had higher overall rates of social deviance in general—40.5% of tweets in the top 20% from New York Post referenced socially deviant events, and the New York Daily News wasn’t far behind. The Wall Street Journal had some of the lowest rates of reporting on social deviance, just 7.7% of the tweets we analyzed; bankers must not break social norms, right?

We also ranked all of the words in the deviant headlines to see if there were any that were particularly predictive of retweets. The most predictive won’t surprise you: When it bleeds it tweets.

Words like "police," "cops," "arrest," "shooting," and "attack" as well as titillations like "porn" and "sex" all boosted retweets. The least predictive words included "accuser," "lawyer," "guilty," "sues," "charge," "allegation," "sentence," and "jury"—clearly related to court proceedings—as well as some others referring to fatality, such as "suicide," "death," and "slaying." Unless it refers to a celebrity (which is an entirely different story), this makes sense: Court dates and suicides aren’t things that we generally feel a need to share around widely to our friends and followers.

The two outlets that bucked the overall trend between social deviance and retweets, the Wall Street Journal and Chicago Tribune, did tend to use many of the court-related words listed above more often than the other outlets we analyzed. Even though they’re covering deviant news events, the ones they focus on aren’t particularly arousing for their audience, at least when it comes to retweeting.

But of course these news events may still have relevance to the communities they affect. Just because a news item wasn’t retweeted doesn’t mean it wasn’t read—more data and further study is needed here to parse out the nuances and differences between what makes news and what makes social news.

There are many other reasons why social media users might share some piece of content besides social deviance: Maybe it’s just funny, or maybe you’re trying to look smart in front of your friends.

But as with emotion and sentiment, social deviance does seem to be another piece of the equation that helps explain the viral sharing of online news content. Like their professional news counterparts, social media users are particularly drawn to (and tend to want to retweet) content that somehow tests the boundaries of what is socially acceptable behavior.

Nick Diakopoulos is a Tow Fellow at the Columbia University Journalism School working on applications of data and computational journalism. He is also a consultant specializing in research, design, and development for computational media applications. Areas of expertise include data visualization, social computing, and news. Find him on Twitter: @ndiakopoulos

[Image: Flickr user Victor]




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