How Does Empowering Users with Greater System Control Affect News Filter Bubbles?


  • Ping Liu LinkedIn Corporation
  • Karthik Shivaram Tulane University
  • Aron Culotta Tulane University
  • Matthew Shapiro Illinois Institute of Technology
  • Mustafa Bilgic Illinois Institute of Technology



While recommendation systems enable users to find articles of interest, they can also create "filter bubbles" by presenting content that reinforces users' pre-existing beliefs. Users are often unaware that the system placed them in a filter bubble and, even when aware, they often lack direct control over it. To address these issues, we first design a political news recommendation system augmented with an enhanced interface that exposes the political and topical interests the system inferred from user behavior. This allows the user to adjust the recommendation system to receive more articles on a particular topic or presenting a particular political stance. We then conduct a user study to compare our system to a traditional interface and found that the transparent approach helped users realize that they were in a filter bubble. Additionally, the enhanced system led to less extreme news for most users but also allowed others to move the system to more extremes. Similarly, while many users moved the system from extreme liberal/conservative to the center, this came at the expense of reducing political diversity of the articles shown. These findings suggest that, while the proposed system increased awareness of the filter bubbles, it had heterogeneous effects on news consumption depending on user preferences.




How to Cite

Liu, P., Shivaram, K., Culotta, A., Shapiro, M., & Bilgic, M. (2024). How Does Empowering Users with Greater System Control Affect News Filter Bubbles?. Proceedings of the International AAAI Conference on Web and Social Media, 18(1), 943-957.