Artificial Intelligence in Digitalized News Media: A Case Study on Implementing Recommender Systems to Retain High Priority Consumers at Ekstra Bladet

Abstract

Digitalization has influenced the consumption of news media and the democratic corporatist model. Simultaneously recommender systems are becoming an inherent part of consumers' everyday life as well as the concern for ‘filter bubbles’ being created. On the other hand, recommender systems are providing useful to the consumer helping them navigate through the information overload of today’s society. Ekstra Bladet is currently working on developing and implementing such recommender systems as a part of the Platform Intelligence in News (PIN) project. To investigate how the consumers of the Danish news media are perceiving this technology, this study poses the research question: How can Ekstra Bladet implement recommender systems to retain high priority consumers?
Adapting an interpretive research philosophy and an inductive approach to collecting empirical data enables an understanding of how the phenomena of interest are perceived among stakeholders and consumers. As a research strategy, a single case study was applied by performing qualitative interviews with experts and high priority consumers of Ekstra Bladet. Furthermore, the data collected were analyzed by consolidating codes and concepts into aggregated dimensions. The findings contribute to the field of perception of recommender systems in Danish news media in relation to the PIN Project where a limited research has been done.
In conclusion, high priority consumers are positive towards the implementation of recommender systems at Ekstra Bladet’s digital platform. However, the consumer expresses concern about ‘filter bubbles’ and data collection, even though personal data is needed for the recommender systems to personalize content to the consumers. There is no correlation between which consumer segment the respondents are in, but rather a tendency in relation to gender as the female respondents are concerned with their data being collected and the male respondents are indifferent. Among both consumer segments there exists a paradox between wanting personalized content recommended and the unwillingness of allowing more than ‘only necessary cookies’. Furthermore, it can be concluded that the consumer segments are different, hence their consumption of news is different. Thus, this should serve as an underlying premise for having different approaches when implementing recommender systems at Ekstra Bladet and recommending content to different consumer segments.