MISINFORMATION Online Misinformation Most Likely to Be Believed by Ideological Extremists: Study
There has been a dramatic rise of online misinformation, but the influence of misinformation is not universal. Rather, users with extreme political views are more likely than are others to both encounter and believe false news.
Political observers have been troubled by the rise of online misinformation—a concern that has grown as we approach Election Day. However, while the spread of fake news may pose threats, a new study finds that its influence is not universal. Rather, users with extreme political views are more likely than are others to both encounter and believe false news.
“Misinformation is a serious issue on social media, but its impact is not uniform,” says Christopher K. Tokita, the lead author of the study, conducted by New York University’s Center for Social Media and Politics (CSMaP).
The findings, which appear in the journal PNAS Nexus, also indicate that current methods to combat the spread of misinformation are likely not viable—and that the most effective way to address it is to implement interventions quickly and to target them toward users most likely to be vulnerable to these falsehoods.
“Because these extreme users also tend to see misinformation early on, current social media interventions often struggle to curb its impact—they are typically too slow to prevent exposure among those most receptive to it,” adds Zeve Sanderson, executive director of CSMaP.
Existing methods used to assess the exposure to and impact of online misinformation rely on measuring views or shares. However, these fail to fully capture the true impact of misinformation, which depends not just on spread, but also on whether users actually believe the false information.
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“Because…extreme users also tend to see misinformation early on, current social media interventions often struggle to curb its impact—they are typically too slow to prevent exposure among those most receptive to it.”
— Zeve Sanderson, executive director of NYU’s Center for Social Media and Politics
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To address this shortcoming, Tokita, Sanderson, and their colleagues developed a novel approach using Twitter (now “X”) data to estimate not just how many users were exposed to a specific news story, but also how many were likely to believe it.
