Customizable Political News Content A Danger To Democracy, Study Claims

BUFFALO — It’s no secret that political news junkies typically frequent the websites that tend to support the party they associate with, and customize their social media feeds so that the headlines they see come from such outlets. Yet a recent study claims that sites that allow you to pick-and-choose the content you read based on your leaning are actually hurting American democracy.

Ivan Dylko, an assistant professor of communication at the University of Buffalo and expert on the effects of communication technology on politics, studied the political effects of customizability — a now-ubiquitous technology that personalizes the subject matter of content on a given information site.

Twitter, Facebook, and Google News all use this technology to sort through news and opinion pieces to deliver information that they deem useful to their users.

Person reading newspaper
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The problem, according to Dylko and his team, is that people are relying on these customizability platforms for all of their news and information. This is creating a space where informed, challenging debate is increasingly difficult.

The study found that most political websites that either customize content for each user automatically or allow the user to create personalized content profiles increase the tendency of users to only consume information that fits in with their political ideologies. The researchers found that this effect was particularly acute in those with moderate political ideologies.

“The increasingly popular personalization tools are likely to lead to a situation where we are surrounded by like-minded information that creates skewed perception of reality, incorrect beliefs, extreme attitudes and suboptimal political behavior,” explains Dylko in a university media release.

Dylko enlisted Igor Dolgov, associate professor psychology at New Mexico State University, and his team of graduate and post-graduate students for the study. They gave a select group of study participants a political survey to determine their individual political leanings. The subjects were then randomly assigned one of four different political websites with liberal and conservative content.

Each site had a different method of aggregating and curating personalized content: a user-customizable site, a system-customizable site on which the researchers manipulated content  based on survey responses, a hybrid of the first two customizable sites, and a non-customizable site. The researchers recorded the links clicked and the time spent reading each article.

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“We found that presence of customizability technology increased consumption of pro-attitudinal information and decreased consumption of counter-attitudinal information,” says Dylko.

He added that this phenomenon is known to increase the polarization of political thought. In essence, using customizable news and opinion sites creates information bubbles that are difficult to disturb and challenge.

“That’s not good for a healthy democracy,” he says. “Living in ideological cocoons prevents cross-fertilization of political ideas, undermines civil political discourse, and hurts the quality of decision making in political context.”

As for what could be done to help alleviate the problem, Dylko says search engines and social media sites should consider ensuring visitors are exposed to news from all corners of the political arena.

“We hope decision makers behind websites like Google, Facebook, Twitter and other key gatekeepers of political information will take note of the unintended harm their services might be inflicting on our society and try to mitigate this harm technologically,” he says.

Of course, news consumers should also consider how websites may feature slanted content and be open to other mediums, Dylko adds.

“We all should be more alert to how information algorithms might inadvertently negatively affect us,” he continues, “and try to break out of the comfortable information bubbles each of us has created on various online news and social media platforms.”

Dylko and his team published their study in August in the journal Computers in Human Behavior.

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