Explaining Online News Engagement Based on Browsing Behavior : Creatures of Habit?
Explaining Online News Engagement Based on Browsing Behavior : Creatures of Habit?
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2020
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Social Science Computer Review ; 38 (2020), 5. - pp. 616-632. - Sage. - ISSN 0894-4393. - eISSN 1552-8286
Abstract
Understanding how citizens keep themselves informed about current affairs is crucial for a functioning democracy. Extant research suggests that in an increasingly fragmented digital news environment, search engines and social media platforms promote more incidental, but potentially more shallow modes of engagement with news compared to the act of routinely accessing a news organization’s website. In this study, we examine classic predictors of news consumption to explain the preference for three modes of news engagement in online tracking data: routine news use, news use triggered by social media, and news use as part of a general search for information. In pursuit of this aim, we make use of a unique data set that combines tracking data with survey data. Our findings show differences in predictors between preference for regular (direct) engagement, general search-driven, and social media–driven modes of news engagement. In describing behavioral differences in news consumption patterns, we demonstrate a clear need for further analysis of behavioral tracking data in relation to self-reported measures in order to further qualify differences in modes of news engagement.
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320 Politics
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news use, tracking data, survey data, social media, information search
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MÖLLER, Judith, Robbert Nicolai VAN DE VELDE, Lisa MERTEN, Cornelius PUSCHMANN, 2020. Explaining Online News Engagement Based on Browsing Behavior : Creatures of Habit?. In: Social Science Computer Review. Sage. 38(5), pp. 616-632. ISSN 0894-4393. eISSN 1552-8286. Available under: doi: 10.1177/0894439319828012BibTex
@article{Moller2020-10Expla-54260, year={2020}, doi={10.1177/0894439319828012}, title={Explaining Online News Engagement Based on Browsing Behavior : Creatures of Habit?}, number={5}, volume={38}, issn={0894-4393}, journal={Social Science Computer Review}, pages={616--632}, author={Möller, Judith and van de Velde, Robbert Nicolai and Merten, Lisa and Puschmann, Cornelius} }
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