Epistemic Overconfidence in Algorithmic News Selection
Abstract: The process of news consumption has undergone great changes over the past decade: Information is now available in an ever-increasing amount from a plethora of sources. Recent work suggests that most people would favor algorithmic solutions over human editors. This stands in contrast to public and scholarly debate about the pitfalls of algorithmic news selection - i.e., the so-called "filter bubbles". This study therefore investigates reasons and motivations which might lead people to prefer algorithmic gatekeepers over human ones. We expect that people have more algorithmic appreciation when consuming news to pass time, entertain oneself, or out of escapism than when using news to keep up-to-date with politics (H1). Secondly, we hypothesize the extent to which people are confident in their own cognitive abilities to moderate that relationship: When people are overconfident in their own capabilities to estimate the relevance of information, they are more likely to have higher levels
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Veröffentlichungsversion
begutachtet (peer reviewed)
In: Media and Communication ; 9 (2021) 4 ; 182-197
- Ereignis
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Veröffentlichung
- (wo)
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Mannheim
- (wer)
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SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- (wann)
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2021
- Urheber
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van der Velden, Mariken
Loecherbach, Felicia
- DOI
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10.17645/mac.v9i4.4167
- URN
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urn:nbn:de:101:1-2023010509441500459306
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:28 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- van der Velden, Mariken
- Loecherbach, Felicia
- SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
Entstanden
- 2021