Scientific research breaks down viral content on Facebook, Twitter

By Grzegorz Piechota

Harvard University

Cambridge, Massachusetts, USA

Connect      

After the recent changes in Facebook algorithms, it may be more important than ever to encourage organic sharing among news media users rather than just push from publishers’ Pages.

So what makes people share?

The decline in an individual user’s engagement and the flood of content from brands triggered several major tweaks to News Feed algorithms in recent years, most recently in June.

Published pieces that go viral often have users that communicate across multiple social platforms.
Published pieces that go viral often have users that communicate across multiple social platforms.

Facebook decided to prioritise private posts and suppress posts by Pages of brands and digital publishers. The reason: to give more space at the top of the News Feed for stories about its users’ private lives and news stories recommended by other users.

The top positions are the most valuable, as the click rate on the News Feed declines rapidly and dips below 10% after the 10th story in the feed, according to internal data disclosed by Facebook-employed scientists in the supplement to its Science journal article on ideological polarisation effects within the network.

Publishers may boost their reach by paying Facebook to bump up one or more scores used by the platform’s algorithms, and/or they can try to make people share their news stories. In other words, they can try to make their content viral.

When a message becomes a virus

The concept of information spreading like a virus was first coined by pop culture writer Douglas Rushkoff in his 1994 book Media Virus. The term “viral marketing” was introduced by my beloved Harvard Business School professor Jeffrey Rayport in a 1996 article published in Fast Company magazine.

Both authors observed alternative ways to spread messages beyond the traditional top-down media communication. Both found that new technologies and cultural shifts allowed communities to keep themselves informed by sharing content or advertising among their members.

After reaching the tipping point, a velocity of the spread of information reminded them of an epidemic. Hence the “virus” in their concepts’ definitions.

Professor Rayport wrote that viral marketing is the most successful when:

  • It is stealthy in the way it approaches potential targets (people who will share the message).

  • It offers something free but valuable upfront (e.g. sampling of paid offers).

  • It exploits the natural behaviour of members of its target communities (e.g. helping others, warning them).

  • It doesn’t look like a virus, so it avoids eliciting initial negative reactions from the target group.

  • It reaches a tipping point — the point at which growth mimics the behaviour of the virus.

Since the publications by Rushkoff and Rayport, many scientists have studied both motivations of users who share news in social media and general patterns of content they actually share. They give complementary ideas about what drives the sharing behaviour.

Users’ motivations

Multiple studies showed that main motives for sharing may be self-serving, altruistic, and social (for example, “What Drives Immediate and Ongoing Word-of-Mouth?”):

  • People admit they share information to gain reputation and establish their influential positions as opinion leaders. In particular, users who prefer hard news are more likely to share them in social media.

  • Some people say they share because they just want others to know, or they want to help them, or they want to entertain them. 

  • Some people use content to socialise with others; they share but they also expect reciprocation, so they treat their networks as exchanges of information.

What people share online

Multiple studies suggest sharing might be more than just about self-representation or value exchange.

  • While common wisdom suggests that people tend to pass along negative news more than positive news, academics found that positive news was actually more viral. But they also found that the relationship between emotions and virality is more complex.

  • Online content that stimulated high-arousal emotions was more viral, regardless of whether those emotions were of a positive (e.g. joy or awe) or negative (e.g. anger or anxiety) nature. Content that evoked more of a deactivating emotion (e.g. sadness), however, was less likely to be viral. 

  • Additionally, they demonstrated that practically useful, interesting, and surprising content was more viral.

Monkey see, monkey do

Facebook data scientists looked at other factors, like the design of sharing experience, affecting spread of information in social media.

A 2012 study showed that users of News Feed were most likely to share a link if they observed that many of their friends had shared it already. And they were doing it almost immediately, much sooner than those who decided to share the link by applying their own judgment only.

As an old West African proverb suggests, “monkey see, monkey do.”

Six principles of contagiousness

One of scientists mentioned above, Wharton professor Jonah Berger, expanded his research on content virality, reviewed all other research available, and in 2013 published Contagious, a classic on viral marketing. It’s a great primer on making all things, including content, viral.

After analysing hundreds of contagious messages, products, and ideas, Berger listed six ingredients that caused things to be talked about or shared:

  1. Social currency: How does it make people look to talk about our content? Most people would rather look smart than dumb, rich than poor, and cool than geeky. It reminds me of an article titled “How Walking in Nature Changes the Brain” from the top-20 most-shared New York Times’ stories of 2015, as recollected by Newswhip, a social analytics company. 

  2. Triggers: How do we remind people to talk about our content? By stimulating their top-of-mind associations through linking content to people’s environments such as personal experiences, familiar people, places, or objects. These might explain the popularity of BuzzFeed’s stories like “21 Things You’ll Only Know If You’re From Northern Illinois.”

  3. Emotions: When people care, they share, regardless of whether content is positive or negative. Awe, excitement, and amusement (humour) activate people and increase sharing. Contentment relaxes and decreases sharing. Anger and anxiety kindle the fire and increase sharing but sadness deactivates and decreases sharing. How does your content make people feel?

  4. Public: Can people see when others are engaging with our content? It’s hard to copy the behaviour you can’t see. Making things like reactions, sharing, or commenting more observable makes them easier to imitate, which makes them more likely to become popular.

  5. Practical value: How can we craft content that seems useful? People like to help others, so if we can show them how our content will save time, improve health, or save money, they’ll spread the word.

  6. Stories: What broader narrative can we wrap our idea in? People don’t just share information, they tell stories. We need to make our message integral to the narrative people themselves try to tell. This insight could explain why people wish to share news articles that confirm their views on the world — they express and prove things they believe and wish to tell others. An example from The New York Times most shared stories of 2015 is “All Politicians Lie. Some Lie More Than Others.”

Trees in the social forest

BuzzFeed, a news organisation that optimises its content for the social Web, created an internal tool to follow the spread of content across social networks, messaging systems, news sites, and blogs.

In 2015, BuzzFeed’s publisher Dao Nguyen, a data scientist herself, published some findings about virality patterns of one of its most successful stories ever: the one asking readers “What Colors Are This Dress?” (the article has enjoyed 37 million views since its publication on 26 February 2015).

Nguyen and her researchers tracked how the story spread from Twitter into Facebook and some other Web sites like blogs and publications.

The lesson here might be to understand that every social network (like Twitter) has members who act like connectors between this one and other networks (like Facebook). We don’t know who they are exactly, but we know they are important to boost virality of a story.

Each of these multi-platform users creates her own tree of people picking up the story and linking to it. Therefore, virality is not about growing just one tree; it’s about planting a forest.

My advice, then, to make a story spread like a virus would be to engage several platforms instead of focusing on just one of them. So, even if we care only about the viral effect on Facebook, we may need to deploy Twitter or other platforms to make it happen.

About Grzegorz Piechota

By continuing to browse or by clicking “ACCEPT,” you agree to the storing of cookies on your device to enhance your site experience. To learn more about how we use cookies, please see our privacy policy.
x

I ACCEPT