Social Media and Belief in Misinformation in Mexico: A Case of Maximal Panic, Minimal Effects?

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Abstract

Contrary to popular narratives, it is not clear whether using social media for news increases belief in political misinformation. Several of the most methodologically sound studies find small to nonexistent effects. However, extant research is limited by focusing on few platforms (usually Facebook, Twitter or YouTube) and is heavily U.S. centered. This leaves open the possibility that other platforms, such as those that rely on visual communication (e.g., Instagram) or are tailored to strong-tie network communication (e.g., WhatsApp), are more influential. Furthermore, the few studies conducted in other countries suggest that social media use increases political misperceptions. Still, these works use cross-sectional designs, which are ill suited to dealing with omitted variable bias and temporal ordering of processes. Using a two-wave survey fielded in Mexico during the 2021 midterm elections (N = 596), we estimate the relationship between frequency of news exposure on Facebook, Twitter, YouTube, Instagram and WhatsApp, and belief in political misinformation, while controlling for both time-invariant and time-dependent individual differences. In contrast to political discussion, information literacy and digital skills, none of the social platforms analyzed exhibits a significant association with misinformed beliefs. We also tested for possible indirect, moderated, and reciprocal relationships, but none of these analyses yielded a statistically significant result. We conclude that the study is consistent with the “minimal media effects” paradigm, which suggests that efforts to address misinformation need to go beyond social platforms.

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Social Media and Fake News in the 2016 Election

Hunt Allcott, Matthew Gentzkow (2017)

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Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning

Gordon Pennycook, David Rand (2018)

Why do people believe blatantly inaccurate news headlines ("fake news")? Do we use our reasoning abilities to convince ourselves that statements that align with our ideology are true, or does reasoning allow us to effectively differentiate fake from real regardless of political ideology? Here we test these competing accounts in two studies (total N = 3446 Mechanical Turk workers) by using the Cognitive Reflection Test (CRT) as a measure of the propensity to engage in analytical reasoning. We find that CRT performance is negatively correlated with the perceived accuracy of fake news, and positively correlated with the ability to discern fake news from real news - even for headlines that align with individuals' political ideology. Moreover, overall discernment was actually better for ideologically aligned headlines than for misaligned headlines. Finally, a headline-level analysis finds that CRT is negatively correlated with perceived accuracy of relatively implausible (primarily fake) headlines, and positively correlated with perceived accuracy of relatively plausible (primarily real) headlines. In contrast, the correlation between CRT and perceived accuracy is unrelated to how closely the headline aligns with the participant's ideology. Thus, we conclude that analytic thinking is used to assess the plausibility of headlines, regardless of whether the stories are consistent or inconsistent with one's political ideology. Our findings therefore suggest that susceptibility to fake news is driven more by lazy thinking than it is by partisan bias per se - a finding that opens potential avenues for fighting fake news.

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The spreading of misinformation online.

Michela Del Vicario, Alessandro Bessi, Fabiana Zollo … (2016)

The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15--where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., "echo chambers." Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades' size.