Can Filter Bubbles Protect Information Freedom? Discussions of Algorithmic News Recommenders in Eastern Europe

The increasing use of recommender systems to provide personalized news delivery influences media worldwide. Using different data sources predict what content will be interesting for specific readers, can better accommodate individual information needs, but also raise concerns about potential audience fragmentation. However, current assessments the effects personalization are predominantly based on observations from Western democracies. This Western-centric approach raises these assessments’ applicability other contexts, in particular non-democratic ones, and brings question influence prevalent conceptualisations (e.g., filter bubbles) attitudes towards it non-Western countries. To address this gap, we scrutinize discussions promises threats countries characterized by limited press freedom: Belarus, Russia Ukraine. document analysis, examine how three categories actors—academics, journalists IT specialists—discuss ways affect public sphere. Through our analysis uncover interact with whether existing applicable contexts.