The Public Service Approach to Recommender Systems: Filtering to Cultivate

Online media consumption has been radically transformed by how companies algorithmically recommend content to their users. Public service (PSM) have also realized the potential of recommender systems and are increasingly using these technologies personalize online offering. PSM on other hand required disseminate diverse content, which can be incompatible with logics commercial that primarily seek drive up consumption. Drawing previous research selective exposure diversity, this study presents results from interviews ten informants across Europe, revealing data scientists within organizations highly aware effects recommendations consumption, design services accordingly. This contributes in-depth knowledge diversity interpreted at operational levels in being adapted a non-commercial setting.