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Recommender systems are increasingly applied by traditional news organisations to structure and personalise their websites according to a set of predefined principles. But we have little insight into the people and processes involved in defining these principles and transforming them into code, despite their direct impact on online news selection and distribution. This article contributes to filling this research gap by investigating recommender system development and implementation at two Scandinavian news organisations. Drawing on field theory, the study explores the powerful position of developers and data scientists within news organisations and their working relationships around algorithmic curation. These new entrants into the field bring new forms of cultural capital and a performance-oriented doxa that clashes with the journalistic doxa, causing delays in the integration of the technology. The article highlights the important role of steering groups and bridging employees in balancing technical, commercial, and editorial concerns but also illuminates the lack of sustained collaboration between journalists and data scientists. Such overlapping and non-siloed collaboration can help build common ground and inter-field understanding and ease technology integration. To this end, the article suggests that long-term business objectives bridge the tech-editorial gap by bringing these different stakeholders together around a common goal.

Bridging the Tech-Editorial Gap: Lessons from Two Case Studies of the Development and Integration of Algorithmic Curation in Journalism