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      Processing news on social media. The political incidental news exposure model (PINE)

      1 , 1 , 1 , 2
      Journalism
      SAGE Publications

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          Abstract

          This article outlines the Political Incidental News Exposure Model. The Political Incidental News Exposure Model understands incidental news exposure as a dynamic process and distinguishes two levels of incidental news exposure: the passive scanning of incidentally encountered political information (first level) and the intentional processing of incidentally encountered content appraised as relevant (second level). After encountering political information incidentally, recipients briefly check the content for relevance (i.e., first level). If content is appraised as relevant, recipients switch to more intensive processing (i.e., second level incidental news exposure). Importantly, second-level incidental news exposure is assumed to have stronger effects on political outcome variables like participation and knowledge than first-level incidental news exposure. The Political Incidental News Exposure Model further acknowledges intention-based (i.e., incidental news exposure while not looking for political news) and topic-based incidental news exposure (i.e., incidental news exposure while looking for other political news) and it conceptualizes incidental news exposure with respect to political and non-political content. Theoretical and methodological implications are discussed.

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          Most cited references42

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          The Rise and Fall of Social Problems: A Public Arenas Model

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            Are people incidentally exposed to news on social media? A comparative analysis

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              Curated Flows: A Framework for Mapping Media Exposure in the Digital Age

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                Author and article information

                Journal
                Journalism
                Journalism
                SAGE Publications
                1464-8849
                1741-3001
                August 2020
                May 16 2020
                August 2020
                : 21
                : 8
                : 1031-1048
                Affiliations
                [1 ]University of Vienna, Austria
                [2 ]MCI Management Center Innsbruck, Austria
                Article
                10.1177/1464884920915371
                4fb5cd8c-a744-4147-9a9d-1d0a9a17a3eb
                © 2020

                https://creativecommons.org/licenses/by-nc/4.0/

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