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We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero. [ABSTRACT FROM AUTHOR]

The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively “unimportant” story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others’ political identities. Observational follow network data collected on Twitter support this prediction: We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be “unimportant” news at the expense of missing out on subjectively “important” news far more frequently. This suggests that “echo chambers”—to the extent that they exist—may not echo so much as silence. [ABSTRACT FROM AUTHOR]

We examine the role of overconfidence in news judgment using two large nationally representative survey samples. First, we show that three in four Americans overestimate their relative ability to distinguish between legitimate and false news headlines; respondents place themselves 22 percentiles higher than warranted on average. This overconfidence is, in turn, correlated with consequential differences in real-world beliefs and behavior. We show that overconfident individuals are more likely to visit untrustworthy websites in behavioral data; to fail to successfully distinguish between true and false claims about current events in survey questions; and to report greater willingness to like or share false content on social media, especially when it is politically congenial. In all, these results paint a worrying picture: The individuals who are least equipped to identify false news content are also the least aware of their own limitations and, therefore, more susceptible to believing it and spreading it further. [ABSTRACT FROM AUTHOR]

What role do ideologically extreme media play in the polarization of society? Here we report results from a randomized longitudinal field experiment embedded in a nationally representative online panel survey (N = 1,037) in which participants were incentivized to change their browser default settings and social media following patterns, boosting the likelihood of encountering news with either a left-leaning (HuffPost) or right-leaning (Fox News) slant during the 2018 US midterm election campaign. Data on 19 million web visits by respondents indicate that resulting changes in news consumption persisted for at least 8 wk. Greater exposure to partisan news can cause immediate but short-lived increases in website visits and knowledge of recent events. After adjusting for multiple comparisons, however, we find little evidence of a direct impact on opinions or affect. Still, results from later survey waves suggest that both treatments produce a lasting and meaningful decrease in trust in the mainstream media up to 1 y later. Consistent with the minimal-effects tradition, direct consequences of online partisan media are limited, although our findings raise questions about the possibility of subtle, cumulative dynamics. The combination of experimentation and computational social science techniques illustrates a powerful approach for studying the long-term consequences of exposure to partisan news. [ABSTRACT FROM AUTHOR]

Widespread belief in misinformation circulating online is a critical challenge for modern societies. While research to date has focused on psychological and political antecedents to this phenomenon, few studies have explored the role of digital media literacy shortfalls. Using data from preregistered survey experiments conducted around recent elections in the United States and India, we assess the effectiveness of an intervention modeled closely on the world’s largest media literacy campaign, which provided “tips” on how to spot false news to people in 14 countries. Our results indicate that exposure to this intervention reduced the perceived accuracy of both mainstream and false news headlines, but effects on the latter were significantly larger. As a result, the intervention improved discernment between mainstream and false news headlines among both a nationally representative sample in the United States (by 26.5%) and a highly educated online sample in India (by 17.5%). This increase in discernment remained measurable several weeks later in the United States (but not in India). However, we find no effects among a representative sample of respondents in a largely rural area of northern India, where rates of social media use are far lower. [ABSTRACT FROM AUTHOR]