Study asks whether reporters are influenced by who they follow on Twitter

Do the people you follow on Twitter—your “followership”—influence your work as a journalist?

According to a first-of-its-kind study conducted by a team of researchers at Northeastern University, there is “a modest correlation between the ideologies of who a journalist follows on Twitter and the content he or she produces.” Of course, correlation isn’t causation, so the question will require more research for a definitive answer.

The study, released this week, looked at 1,000 journalists at 25 news media outlets, along with all of the people the reporters follow on Twitter, and the half a million news articles they collectively produced.

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“We know journalists are spending an enormous amount of time on Twitter,” John Wihbey, an assistant professor at Northeastern and one of four authors of the study, tells CJR. “It’s at once a water cooler for journalists, but it’s also an important place where we’re spending a lot of time. We wanted to take individual journalists and say, ‘Is there any correlation between the ideological leaning of the people they follow and their published output?’”

The data shows journalists from right-leaning outlets usually have a right-leaning followership (those they follow), while those from left-leaning outlets tend to have a left-leaning followership. While some might say, “isn’t that obvious?” Wihbey points out no one has ever been able to quantify the point before, and it’s an important first step to understanding Twitter and its impact.

It’s at once a water cooler for journalists, but it’s also an important place where we’re spending a lot of time.”

What they found is a “statistically significant correlation,” though Wihbey stresses “it’s not causation.” The danger is that those follower sets are potentially restricting what could be a more diverse diet of ideas for the journalists.

“Overall, I think what it is is a reminder that, ‘Hey, if we’re gonna spend a lot of time in this platform, it could shape how we see the world and frame the issues.’”

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Wihbey and his team recognize that journalists have specific beats—so following a lot of Republicans isn’t extraordinary when the beat is Republicans in Congress, even if the journalist works at a left-leaning publication.

Taking into account those beats, and controlling for them and the political leanings of the outlets journalists work for, by using big-data tools, Wihbey says they were able to “let the numbers do the talking.”

Wihbey recognizes that “it’s a dangerous time to talk about journalist bias” and stresses that the people you follow on Twitter—you’re choosing to follow them, after all—are not causing you to be left or right leaning. The study notes that “journalists as a whole are more likely to be left-leaning” and that there are a number of reasons why, including that “journalists are generally concentrated in metropolitan areas.”

The study, says Wihbey, is a call to be mindful that whether you’re a journalist at a left-leaning or right-leaning outlet perhaps there is room to diversify your Twitter followership. Otherwise, the people you are following may be reinforcing the silo you inhabit.

“I think it’s ultimately important to be aware of the information universe we are drawing on as journalists. Process-wise, we should always be aware of the possible bias that could slip in,” Wihbey says.

The research looked at the Washington Times, Breitbart, and the National Review among others as “Heavily Right Leaning;” Huffington Post, Vox, and the The New Yorker among those considered “Heavily Left Leaning;” the New York Post, Oklahoman, the Florida Times-Union, and the Orange County Register among “Right Leaning;” and USA Today, Bloomberg, BuzzFeed News, and The New York Times as among those it considers “Left Leaning.” They identified where on the spectrum an outlet is by scoring the ideologically informative terms used, and the frequency of that use.

Researchers also accounted for terms journalists use in their work to determine “Left-Leaning” or “Right-Leaning,” including “equal pay,” “voting rights act,” “marriage equality,” “mandates,” “deal with Iran,” “overreach,” and “illegal immigrants.” The terms fall as you probably expect: The first three in this list scale “Left,” and the last four scale “Right.” The researchers point to studies that show “partisan terms can be used to identify at least some level of partisanship in writing,” and note that their results “do align outlets at political extremes correctly relative to each other.” Of the phraseology they examined, they settled on accounting for 114 terms—57 right-leaning and 57 left-leaning.

The data also shows some exceptions to the norm: David Sanger at The New York Times, for example, has a left-leaning followership, but his national security columns “have more right-wing phraseology,” says Wihbey. “What this shows is even if [the journalist has] a leaning, the professionals—the norms and standards that they uphold—can overcome that potential to bias.” He demonstrates “real down the middle, straight-forward” reporting, he says.

“There aren’t that many that way,” Wihbey adds. “Twitter followership is just a proxy. Just because you’re on Twitter for an hour a day, it’s not the full universe of what you’re consuming.”

Wihbey also says that given big-data capabilities, “there should be a lot more research like this.”

While Wihbey’s study focuses on partisanship, he points to Peter Hamby’s Shorenstein Center paper on the 2012 presidential campaign. “Peter argued [Twitter] led to a superficiality, a greater obsession with trivial things, [treating the election as] a horse race, and diminished the depth of reporting,” says Wihbey, echoing Hamby’s position that Twitter can “create a bubble of journalistic in-crowd concerns and issues.”

Wihbey presented his research at the KDD Data Science + Journalism Workshop/Conference in Halifax on Monday. Download the full report here.

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