New study reveals a sign of dangerously high levels of polarization and how reaction to news coverage may spread and foster online polarization in the United States
According to a new study conducted by Princeton University researchers, people may be unwittingly grouping themselves into divided networks when they customize their internet news feeds.
The researchers created a sophisticated contagions model, which is generally used to examine how behavior spreads in groups, but they applied it to how reactions to news coverage spread and fuel online polarization. They then used Twitter data to evaluate their theoretical model.
When people are less responsive to news, their online world remains politically mixed, according to the researchers. When users continually react to and share items from their favored news sources, however, they are more likely to establish a politically isolated network, or what the researchers refer to as “epistemic bubbles.”
When people are trapped in these bubbles, they lose out on more news stories, including those from their favorite media providers. According to the model, users appear to avoid “unimportant” news at the expense of losing out on subjectively important news.
According to the researchers, all of this could be contributing to America’s unusually high levels of political polarization and societal distrust.
“Our study shows that, even without social media algorithms, coverage from polarized news outlets is changing users’ social connections and pushing them unknowingly into so-called political ‘echo chambers,’ where they are surrounded by others who share their same political identity and beliefs,” says Christopher Tokita, a data scientist at cybersecurity startup Phylum.
“Whether a user chooses to react to or ignore certain news posts can help determine if their social network will become ideologically homogenous or remain more diverse.”
Tokita studied these behaviors in collaboration with Andy Guess, assistant professor of politics and public affairs at the Princeton School of Public and International Affairs, and Corina Tarnita, professor of ecology and evolutionary biology at the Princeton Department of Ecology and Evolutionary Biology, by developing a theoretical model and testing its predictions with data from real social networks on Twitter.
The concept of “information cascades,” or the process of individuals seeing and replicating the activities of others, was central to their modeling. This is similar to the collective activity seen in schools of fish or insect swarms.
They delve deeper into this topic, demonstrating how the sharing of viral news items can cause consumers to believe that some of their “friends” on social media are distorting the news as reported by their favored channels. Users accidentally sort themselves into polarized networks when they “unfollow” untrustworthy connections, therefore constructing their own online social circles.
They then put the algorithm to the test with Twitter data, looking at 1,000 followers from four different news outlets: CBS News, USA Today, Vox, and the Washington Examiner. They used the whole follower network of users to record who followed and unfollowed each other over a six-week period in summer 2020 to track signs of political ideology and shifting social networks.
Their findings indicated a number of online trends and behaviors that could contribute to political polarization. First, the followers of CBS News and USA Today, two mainstream news channels recognized for consistent fact-based reporting, were more politically diverse than Vox and the Washington Examiner, which, according to the researchers, deliver more slanted and agenda-driven news coverage. Users who followed Vox and the Washington Examiner lost more political and ideological variety among their online relationships than users who followed CBS News and USA Today.
While internet contacts cannot fully explain the polarizing shift in American politics, they have had a significant impact on human behavior and relationships. The study’s findings indicate that explicit knowledge of political ideology or alignment is not required for users’ social networks to become politically separated.
“It’s not hard to find evidence of polarized discourse on social media, but we know less about the mechanisms of how social media can drive people apart. Our contribution is to show that polarization of online social networks emerges naturally as people curate their feeds. Counterintuitively, this can occur even without knowing other users’ partisan identities,” Guess added.
The research team calls for more research into how these tendencies may contribute to the distribution and consumption of “fake news” and disinformation, as well as how inaccurate material drives public political divisiveness. According to the study, people who consume and disseminate bogus news may be unknowingly distancing themselves from everyone else who follows conventional sources. This should be looked at further.
“Though derived from a simple theoretical model of collective dynamics, our results demonstrate the power of a cross-disciplinary approach to the study of political polarization. We hope that they may inspire future examinations into social network-specific algorithms and patterns as potential contributors to societal polarization,” Tarnita said.
Source: Proceedings of the National Academy of Sciences / Princeton University
Image Credit: Getty
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