2018
DOI: 10.1080/1369118x.2018.1444783
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Facebook news and (de)polarization: reinforcing spirals in the 2016 US election

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Cited by 144 publications
(109 citation statements)
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“…The level of algorithmic interference in the creation of echo chambers has been questioned, however. Large-scale studies measuring the impact of algorithm-suggested news on selective exposure and polarization highlight how users' choices are more influential than machine-run activities in the creation of echo chambers (Bakshy et al, 2015;Boxell et al, 2017;Beam et al, 2018). Even though we agree that environmental bias should not be overemphasized in the construction of secluded online spaces, we simultaneously stress how the context in which interactions occur should not be overlooked 2 .…”
Section: Algorithms and Dataveillance: An Onlife Meaning-making Mechamentioning
confidence: 77%
“…The level of algorithmic interference in the creation of echo chambers has been questioned, however. Large-scale studies measuring the impact of algorithm-suggested news on selective exposure and polarization highlight how users' choices are more influential than machine-run activities in the creation of echo chambers (Bakshy et al, 2015;Boxell et al, 2017;Beam et al, 2018). Even though we agree that environmental bias should not be overemphasized in the construction of secluded online spaces, we simultaneously stress how the context in which interactions occur should not be overlooked 2 .…”
Section: Algorithms and Dataveillance: An Onlife Meaning-making Mechamentioning
confidence: 77%
“…Based on various big-data sources, researchers have shown that online social networks are often segregated into social cliques that are characterized by shared worldviews, ideological group memberships, and patterns of information consumption (Bakshy et al, 2015;Del Vicario et al, 2016;Himelboim, Mccreery, & Smith, 2013). Despite this, individuals vary in their motivations to form likeminded online social ties (Häussler, 2018); social media can also encourage users to find diverse information (Beam, Hutchens, & Hmielowski, 2018). This implies that individual differences in how a person relates to online social networks are crucial to understanding online social phenomena.…”
Section: The Identity Bubble Reinforcement Model (Ibrm)mentioning
confidence: 99%
“…Die Forschungsergebnisse insgesamt sind jedoch uneinheitlich. Während eine der seltenen Längsschnittstudien auf Twitter eine depolarisierende Wirkung durch heterogene Netzwerke in verschiedenen Ländern wie den USA, Deutschland und Spanien nachweisen kann (Barberá 2015), liefern Studienüber die Rolle von Facebook konträre und widersprüchliche Ergebnisse (Allcott et al 2019;Beam et al 2018). Auch bezüglich des Internetzugangs insgesamt zeigt sich ein uneinheitliches Bild: Während Tewksbury und Riles (2015) einen Zusammenhang zwischen Internetnutzung und Polarisierung in den USA feststellen, argumentieren Boxell et al (2017), dass politische Polarisierung in den letzten Jahren insbesondere unter denjenigen US-Bürgern zugenommen hat, die mit der geringsten Wahrscheinlichkeit das Internet nutzen.…”
Section: Online-medienkonsum Und Polarisierungunclassified