BeskrivelseWhen public service media adopt algorithmic recommender systems for personalized presentation of content, the conceptualization of public service media and its media obligations are challenged (Sørensen & Hutchinson, 2018). E.g. the exposure of diversity of viewpoints and worldviews which previously was curated by editors now must be expressed in the unambiguous meta-data language of recommender systems (Sørensen & Schmidt, 2016). Other aspects of human editorial curation, such as editorial prioritization must also be expressed in metadata numbers. On the other side, new opportunities in creating targeted exposure and creating audiences must be understood. With Danish Broadcasting Corporation (DR) as case - supported by an outlook to eight other cases of implementation of recommender systems (cf. Sørensen, 2019) - we analyze dilemmas and strategies to combine public service media obligations with recommender algorithms. Over a period of three years we followed, via 13 in-depth interviews with project staff, DR's implementation of a recommender system for its Video on Demand service 'DRTV'. Our findings indicate that traditional editorial control is still maintained and the automated exposure of content only plays a secondary role. The path to automation is not straight forward, every step is taken with care. We also notice organizational tensions between performance-oriented data specialists and traditional editorial staff. Generally, the process of interpreting and domesticating the recommender systems technology exposes structural problem in the public service media (PSM) value proposition: At same time as PSM should be driven by ideals of enlightenment, education and entertainment (cf. e.g. UNESCO, 2001), it must also respond to the materiality of algorithms and key performance indicators (Buchner, 2018). In this way, the process of implementing recommender systems clearly exposes public service organizations' old dilemma of trying both have a good reach and having a specific and distinct purpose in the media landscape (Nissen, 2006). It also highlights the structural tensions between the quantitative and qualitative rationale for public service broadcasting / -media (McManus, 1994; Tracey, 1998).
|Periode||24 sep. 2020|
|Begivenhedstitel||Challenges of Journalism in 21. century – Automated Journalism and AI Journalism|
|Placering||Prague, TjekkietVis på kort|
|Grad af anerkendelse||International|
Algorithmic Public Service Media Content Recommendation
Projekter: Projekt › Forskning