Auditing the Impact of Cross-Site Web Tracking on YouTube Political and Misinformation Recommendations
This addresses the risk of tracking-driven misinformation bubbles for YouTube users, with incremental insights into privacy tools' effectiveness.
The study tackled the problem of how cross-site web tracking influences YouTube's recommendations of political and misinformation content, finding that tracking-permissive environments led to more polarized and misinformation-laden recommendations compared to tracking-restrictive ones.
YouTube has today become the primary news source for many users, which raises concerns about the role its recommendation algorithm can play in the spread of misinformation and political polarization. Prior work in this area has mainly analyzed how recommendations evolve based on users' watch history within the platform. Nevertheless, recommendations can also depend on off-platform browsing activity that Google collects via trackers on news websites, a factor that has not been considered so far. To fill this gap, we propose a sock-puppet-based experimental framework that automatically interacts with news media articles and then collects YouTube recommendations to measure how cross-site tracking affects the political and misinformation content users see. Moreover, by running our audits in both tracking-permissive and tracking-restrictive browser environments, we assess whether common privacy-focused browsers can protect users from tracking-driven political and misinformation bubbles on YouTube.