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      Partisan media, untrustworthy news sites, and political misperceptions

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          Abstract

          This study investigates the potential role both untrustworthy and partisan websites play in misinforming audiences by testing whether actual exposure to these sites is associated with political misperceptions. Using a sample of American adult social media users, we match data from individuals’ Internet browser histories with a survey measuring the accuracy of political beliefs. We find that visits to partisan websites are at times related to misperceptions consistent with the political bias of the site. However, we do not find strong evidence that untrustworthy websites consistently relate to false beliefs. There is also little evidence that visits to less partisan, centrist news sites are associated with more accurate political beliefs about these issues, suggesting that exposure to politically neutral news is not necessarily the antidote to misinformation. Results suggest that focusing on partisan news sites—rather than untrustworthy sites—may be fruitful to understanding how media contribute to political misperceptions.

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          Most cited references41

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          Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

          G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
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              The science of fake news

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                New Media & Society
                New Media & Society
                SAGE Publications
                1461-4448
                1461-7315
                July 28 2021
                : 146144482110333
                Affiliations
                [1 ]University of Michigan, USA
                [2 ]American University, USA
                [3 ]University of California Davis, USA
                [4 ]Universiteit van Amsterdam, The Netherlands
                [5 ]University of California Davis, USA; University of Amsterdam, The Netherlands
                Article
                10.1177/14614448211033300
                f2d02d4d-1d7d-4636-88da-81dc7a9285e7
                © 2021

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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