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Explanations of news personalisation across countries and media types

Author

Listed:
  • Bastian, Mariella
  • Makhortykh, Mykola
  • Harambam, Jaron
  • van Drunen, Max

Abstract

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.

Suggested Citation

  • Bastian, Mariella & Makhortykh, Mykola & Harambam, Jaron & van Drunen, Max, 2020. "Explanations of news personalisation across countries and media types," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 9(4), pages 1-34.
    • Handle: RePEc:zbw:iprjir:225645
    DOI: 10.14763/2020.4.1504
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    Cited by:

    1. Urman, Aleksandra & Makhortykh, Mykola, 2023. "How transparent are transparency reports? Comparative analysis of transparency reporting across online platforms," Telecommunications Policy, Elsevier, vol. 47(3).
    2. Paschalia (Lia) Spyridou & Constantinos Djouvas & Dimitra Milioni, 2022. "Modeling and Validating a News Recommender Algorithm in a Mainstream Medium-Sized News Organization: An Experimental Approach," Future Internet, MDPI, vol. 14(10), pages 1-21, September.

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