Designing personalisation of European public service media (PSM): trends on algorithms and artificial intelligence for content distribution



Palabras clave:

Public service broadcasting, PSM, Recommendation systems, Artificial intelligence, AI, Public service media, Algorithms, Bubble filters, Video on demand, VoD, Journalism, Audiovisual communication, Content distribution, News, Trends, Europe


The migration of audiences to digital environments has motivated the media to develop a content distribution strategy that has a presence in these new spaces. In the case of European public broadcasters, they have strengthened their digital news services and have built video-on-demand platforms where they organise and screen their products. Even so, the overload of information and content reaching users forces corporations to look for new mechanisms to present an adequate, interesting and diverse offering to each of their followers. This research project analyses the use of artificial intelligence in the recommendation systems implemented by 14 European public broadcasters in Germany (ARD and ZDF), Belgium (VRT and RTBF), Denmark (DR), Spain (RTVE), Finland (YLE), France (France TV), Great Britain (BBC), the Netherlands (NPO), Ireland (RTÉ), Italy (RAI), Sweden (SVT) and Switzerland (RTS). The results reveal that there is no unanimity among the corporations with regard to the operation and origin of these systems, which vary between home-made developments, acquired from third parties, or collaborative solutions. Operators differentiate between news recommendation processes and those executed on their VoD platforms and aim to distance their systems from those of commercial media, for which they have already started working on a public service media (PSM) algorithm that includes traditional public media values, avoids filter bubbles, and pays special attention to the European General Data Protection Regulation (GDPR).


Aslama-Horowitz, Minna; Nieminen, Hannu (2017). “Diversity and rights. Connecting media reform and public service media”. IC. Revista científica de información y comunicación, v. 14, pp. 99-119.

Bodo, Bolázs (2018). “Means, not an end (of the world) - The customization of news personalization by European news media”. In: Algorithms, automation, and news conference, Munich, pp. 22-23.

Bozdag, Engin; Van-den-Hoven, Jeroen (2015). “Breaking the filter bubble: democracy and design”. Ethics and information technology, v. 17, pp. 249-265.

Canavilhas, João (2022). “Inteligencia artificial aplicada al periodismo: estudio de caso del proyecto “A European perspective” (UER)”. Revista latina de comunicación social, n. 80.

EBU (2019). News report 2019. The next newsroom. Geneva: European Broadcasting Union.

EBU (2021). Personalisation and recommendation ecosystem developed by broadcasters for broadcasters. Media Intelligence Service. Geneva: European Broadcasting Union.

Fieiras-Ceide, César; Vaz-Álvarez, Martín; Túñez-López, Miguel (2022). “Artificial intelligence strategies in European public broadcasters: Uses, forecasts and future challenges”. Profesional de la información, v. 31, n. 5, e310518.

Fields, Ben; Jones, Rhianne; Cowlishaw, Tim (2018). The case for public service recommender algorithms. In: Fatrec Workshop. London: BBC, pp. 22-24.

García-Orosa, Berta (2022). “Digital political communication: Hybrid intelligence, algorithms, automation and disinformation in the fourth wave”. In: García-Orosa, Berta (ed.). Digital political communication strategies, Palgrave, pp. 3-23. ISBN: 978 3 030 81568 4

Hallin, Daniel C.; Mancini, Paolo (2004). Comparing media systems: Three models of media and politics. Cambridge, UK: Cambridge University Press. ISBN: 978 0 511790867

Herlocker, Jonathan L.; Konstan, Joseph A.; Borchers, Al; Riedl, John (1999). “An algorithmic framework for performing collaborative filtering”. ACM Sigir, v. 22, pp. 230-237.

Jones, Bronwyn; Jones, Rhianne (2019). “Public service chatbots: Automating conversation with BBC News”. Digital journalism, v. 7, n. 8.

Kunert, Jessica; Thurman, Neil (2019). “The form of content personalisation at mainstream, transatlantic news outlets”. Journalism practice, v. 13, n. 7, pp. 759-780.

Möller, Judith; Trilling, Damian; Helberger, Natali; Van-Es, Bram (2018). “Do not blame it on the algorithm: an empirical assessment of multiple recommender systems and their impact on content diversity”. Information, communication & society, v. 21, n. 7, pp. 959-977.

Napoli, Philip M. (2011). “Exposure diversity reconsidered”. Journal of information policy, v. 1, pp. 246-259.

Newman, Nic (2021). Journalism, media, and technology trends and predictions 2021. UK: The Reuters Institute for the Study of Journalism.

Pariser, Eli (2011). The filter bubble: what the Internet is hiding from you. London: Penguin Books. ISBN: 978 0 241954522

Pöchhacker, Nikolaus; Burkhardt, Marcus; Geipel, Andrea; Passoth, Jan-Hendrik (2017). “Interventionen in die produktion algorithmischer öffentlichkeiten: Recommender systeme als herausforderung für öffentlich-rechtliche sendeanstalten”. Kommunikation & gesellschaft, v. 18.

Sanahuja-Sanahuja, Rosana; López-Rabadán, Pablo (2022). “Ética y uso periodístico de la inteligencia artificial. Los medios públicos y las plataformas de verificación como precursores de la rendición de cuentas en España”. Estudios sobre el mensaje periodístico, v. 28, n. 4, pp. 959-970.

Schmidt, Jan-Hinrik; Sørensen, Jannick-Kirk; Dreyer, Stephan; Hasebrink, Uwe (2018). “Wie können empfehlungssysteme zur vielfalt von medieninhalten beitragen? Perspektiven für öffentlich-rechtliche rundfunkanstalten”. Media perspektiven, v. 11, pp. 522-531.

Sørensen, Jannick-Kirk (2013). “PSB goes personal: The failure of personalised PSB web pages”. MedieKultur, v. 29, n. 55, pp. 43-71.

Sørensen, Jannick-Kirk (2019). Public service media, diversity and algorithmic recommendation: Tensions between editorial principles and algorithms in European PSM Organizations. INRA.

Sørensen, Jannick-Kirk; Van-den-Bulck, Hilde (2018). “Public service media online, advertising and the third-party user data business: A trade versus trust dilemma?”. Convergence: The international journal of research into new media technologies, v. 26, n. 2, pp. 421-447.

Thurman, Neil; Lewis, Seth C.; Kunert, Jessica (2019). “Algorithms, automation, and news”. Digital journalism, v. 7, n. 8, pp. 980-992.

Unesco (2001). Public broadcasting why? How? Technical report. Paris: Unesco.

Van-den-Bulck, Hilde; Moe, Hallvard (2017). “Public service media, universality and personalisation through algorithms: mapping strategies and exploring dilemmas”. Media, culture & society, v. 40, n. 6.

YLEisradio (2018). The first of its kind in the world: YLE NewsWatch’s smart Voitto assistant shows recommendations directly on the lock screen. Helsinki: YLE.

Zuiderveen-Borgesius, Frederik; Trilling, Damian; Moeller, Judith; Bodó, Balázs; De-Vreese, Claes H.; Helberger, Natali (2016). “Should we worry about filter bubbles?”. Internet policy review. Journal on internet regulation, v. 5, n. 1.



Cómo citar

Fieiras-Ceide, C., Vaz-Álvarez, M. ., & Túñez-López, M. (2023). Designing personalisation of European public service media (PSM): trends on algorithms and artificial intelligence for content distribution. Profesional De La información, 32(3).



Artificial Intelligence


La descarga de datos todavía no está disponible.


Cargando métricas ...