Concerns over fake news have triggered a renewed interest in various forms of media literacy. Prevailing expectations posit that literacy interventions help audiences to be “inoculated” against any harmful effects of misleading information. This study empirically investigates such assumptions by assessing whether individuals with greater literacy (media, information, news, and digital literacies) are better at recognizing fake news, and which of these literacies are most relevant. The results reveal that information literacy—but not other literacies—significantly increases the likelihood of identifying fake news stories. Interpreting the results, we provide both conceptual and methodological explanations. Particularly, we raise questions about the self-reported competencies that are commonly used in literacy scales.

Despite long-standing concerns over self-reported measures of media use, media research has relied heavily on self-reported data. This study not only examined discrepancies between survey and logged smartphone data but assessed whether correlational outcomes using self-reported measures produce greater or smaller effect sizes compared to outcomes using logged measures. College students (n = 294) and MTurk workers (n = 291) provided self-reported and logged data of smartphone use over seven days. The correlations we examined involved four psychosocial contexts, including bridging, bonding, well-being, and problematic use of smartphones. The results showed that the effect sizes of correlations using self-reported data tend to be smaller compared to those using logged data. We believe that this is a hopeful message to the field. This could mean that extant survey results have not erroneously inflated communication findings and that communication researchers still have a lot to reveal with further refined measures.

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Despite a fast-growing body of literature on fake news and mis-/disinformation, there remains surprisingly little empirical work on the social/political consequences of exposure to false information. Addressing this issue, this study provides initial evidence that perceptions of false information exposure catalyze political cynicism. The findings from a two-wave panel survey during the 2018 US midterm elections reveal that perceptions of false information exposure 2 weeks before the election significantly predict the changes in political cynicism immediately after the election day. We also find that social media news use in Wave 1 significantly relates to political cynicism in Wave 2 indirectly through perceptions of mis-/disinformation exposure. The autoregressive regression model indicates that our findings are robust after controlling for prior levels of cynicism.

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