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https://nbn-resolving.org/urn:nbn:de:0168-ssoar-85333-2

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Explaining Online News Engagement Based on Browsing Behavior: Creatures of Habit?

[Zeitschriftenartikel]

Möller, Judith
Velde, Robbert Nicolai van de
Merten, Lisa
Puschmann, Cornelius

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 mode... mehr

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.... weniger

Thesaurusschlagwörter
Soziale Medien; Nachrichten; Informationsverhalten; Online-Medien; Nutzung; Suchmaschine; Datengewinnung

Klassifikation
interaktive, elektronische Medien
Erhebungstechniken und Analysetechniken der Sozialwissenschaften

Freie Schlagwörter
information search; news use; survey data; tracking data

Sprache Dokument
Englisch

Publikationsjahr
2020

Seitenangabe
S. 616-632

Zeitschriftentitel
Social Science Computer Review, 38 (2020) 5

Heftthema
Integrating Survey Data and Digital Trace Data

DOI
https://doi.org/10.1177/0894439319828012

ISSN
1552-8286

Status
Veröffentlichungsversion; begutachtet (peer reviewed)

Lizenz
Creative Commons - Namensnennung, Nicht-kommerz. 4.0


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Home  |  Impressum  |  Betriebskonzept  |  Datenschutzerklärung
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.