Artikel
Explanations of news personalisation across countries and media types
News outlets worldwide increasingly adopt user- and system-driven personalisation to individualise their news delivery. Yet, the technical implementation of news personalisation systems, in particular the one relying on algorithmic news recommenders (ANRs) and tailoring individual news suggestions with the help of user data, often remains opaque. In our article, we examine how news personalisation is used by quality and popular media in three countries with different media accountability infrastructures - Brazil, the Netherlands, and Russia - and investigate how information about personalisation usage is communicated to the news readers via privacy policies. Our findings point out that news personalisation systems are predominantly treated as black boxes that indicate a significant gap between practice and theory of algorithmic transparency, in particular in the non-EU context.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Internet Policy Review ; ISSN: 2197-6775 ; Volume: 9 ; Year: 2020 ; Issue: 4 ; Pages: 1-34 ; Berlin: Alexander von Humboldt Institute for Internet and Society
- Klassifikation
-
Sozialwissenschaften, Soziologie, Anthropologie
- Thema
-
News personalisation
Privacy policies
Transparency
Accountability
Comparative journalism research
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Bastian, Mariella
Makhortykh, Mykola
Harambam, Jaron
van Drunen, Max
- Ereignis
-
Veröffentlichung
- (wer)
-
Alexander von Humboldt Institute for Internet and Society
- (wo)
-
Berlin
- (wann)
-
2020
- DOI
-
doi:10.14763/2020.4.1504
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Bastian, Mariella
- Makhortykh, Mykola
- Harambam, Jaron
- van Drunen, Max
- Alexander von Humboldt Institute for Internet and Society
Entstanden
- 2020
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