Algorithmic curation of News on YouTube: Evidence from the 2022 French Presidential Campaign
Year: 2025
Type: preprint
Abstract: Debate is growing over how algorithmic recommendations influence news visibility, particularly regarding interest and ideological bias. This study examines YouTube's News Recommender System (NRS), focusing on the French "News" section of the homepage through a large-scale audit using automated browsing agents.Our findings show that the NRS prioritises platform-native creators over established news outlets, favouring content that aligns with YouTube's features rather than traditional editorial standards. Politically charged, opinion-based videos, especially those from prominent figures affiliated with extreme political parties, receive ongoing algorithmic promotion. While centrist and moderate political figures remain underrepresented, the algorithm boosts their visibility once users interact with this type of content. This two-part mechanism, which amplifies already prominent content and appears to overcompensate for rare content, does not just reflect engagement-based optimisation, but is driven by the algorithm's tendency to maintain coherence in a highly unbalanced content landscape. However, this compensatory logic does not counteract the algorithm's broader tendency to promote content from radical political figures while marginalising institutional news outlets. Through this process, the NRS actively reshapes news exposure within the "News" section, privileging political expression over journalistic authority and reproducing structural hierarchies of visibility.
Source: HAL
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7110689079