Elon professor shedding light on web of fake news

When a heavily armed Salisbury man stormed a Washington, D.C., pizza restaurant in search of a child sex ring rumored to be run by Hillary Clinton, the perils of baseless but widely distributed reports known as “fake news” became suddenly real.

By the time of that December incident, Jonathan Albright had spent months immersed in research on the topic, producing several widely distributed graphics representing what he calls the “fake news ecosystem” – a network of websites, social media accounts and other outlets that create, distribute and promote false information in hopes of influencing the public.

As the controversy over fake news continues, Albright, a professor of media analytics at Elon University, has emerged as an expert in the tactics he asserts amount to old-fashioned propaganda using high-tech tools.

In a series of posts on the topic, he presented a visual map of the online hubs where fake news is created and spread to like-minded websites and social media accounts, including fake accounts run by bots. The network allows such reports to spread quickly, earning them top billing on social media sites and search engines that make them seem real.

Albright’s post-election research has been featured in a number of publications, including The Guardian, The Washington Post and Fortune Magazine.

Janna Anderson, who directs the university’s Imagining the Internet Initiative, says Albright has shed new light on an area of emerging importance.

“This kind of data journalism is extremely important,” Anderson says. “He was able to illustrate in a fairly simple manner a lot of information about fake news and move the conversation on this forward in a productive way.”

A scientific outlook

Albright grew up in Alaska and says he was attracted early to both journalism – he worked on his school newspaper – and biology, an interest that would inform his concept of an information ecosystem.

He earned his undergraduate degree in Portland, Oregon, in biology, but soon turned his attention to media studies, particularly in using his science background to explore quantitative questions involved in the growing use of online media.

Much of his research has involved analyzing particular search preferences or trending hashtags on Twitter. He worked briefly at both Google and Yahoo, where he honed his knowledge of media usage.

“I’ve always been interested in social news and how news is propagated socially,” he says. “My recent research put together a lot of what were formerly disparate research interests into one topic.”

He says whether he was studying science or media, his approach has always been exploratory.

“It’s not really expecting or knowing what you’re going to find, but poking around and exploring different data sets,” he says. “For this kind of research, it’s beneficial to have that outlook.”

Albright came to Elon in 2012 to help launch its media analytics major, an unusual focus that allows students to focus on audience analysis, measuring the impact of media messages and using that data to tell stories about how media works.

He was on a research sabbatical this fall when he began the project that would propel him to the international spotlight.

Propaganda machine

As the phrase “fake news” worked its way into the public lexicon this fall, Albright was frustrated that the discussion seemed limited to a few inaccurate articles shared widely through social media.

It was widely believed that these articles, many of which included far-fetched accusations against Democratic presidential candidate Hillary Clinton, had swayed the presidential election. But Albright wanted to know more.

So he scoured a list of acknowledged fake news websites to see how their articles spread through the web. The result, a map of what Albright calls the “fake news ecosystem,” was enlightening.

Starting with a list of about 300 fake news sites, he mapped which sites were linking to them. What emerged was a network of millions of sites that regularly linked to one another, sharing information at a rate that made them rise to the top of search engines and lists of trending topics on social media.

“It shows the information resources they’re using to promote a certain type of view,” he says. “It’s so large and complex, you can’t put it into a table or a list. Things started to fall into place when I looked at it as an ecosystem.”

His picture included large dots and blue or red, denoting whether they catered to Democratic or Republican audiences; the larger dots had the largest audiences. White dots denoted neutral sites, including many large media and government sources.

The red network was far stronger, and bled into the more neutral networks, he found, while the blue dots tended to be more isolated.

In addition, he found that some sites were tracking individuals, following their “likes” on Facebook and other cues and feeding them targeted content based on those preferences.

“This is a propaganda machine,” he says. “It’s targeting them individually to recruit them to an idea.”

While his research shows the system seemed to benefit conservative media groups during last year’s election, Albright says such methods will likely become more widespread.

He envisions several areas of future research, such as how automated social media accounts are amplifying certain voices and how search engines are distorted by automated promotion of fake news content.

He’s particularly interested in pinpointing instances where this kind of proliferation changes public sentiment. In some cases, he says, data on search preferences and popular topics is likely compromised by this kind of automated promotion.

“A lot of this data is distorted because there are millions of accounts that are like drones and republish information,” he says.

The lessons he draws from his research on fake news is not that there should be restrictions on what should be published where. He disagrees with suggestions that search engines and others should step in to limit the content that is available.

Instead, he says, consumers of information need to consider more carefully where each Facebook post, tweet or article originates – and how that’s affecting their views of the world.

“People should develop the skills they need to understand what’s real and fake,” he says. “They also need to consider looking at the other side or find sources of news that at least permit an alternative point of view. A lot of people are definitely getting a very specific or limited angle on news events.”

This story was originally published January 7, 2017 at 2:24 PM with the headline "Elon professor shedding light on web of fake news."