Balanced News Using Constrained Bandit-based Personalization
arXiv:1806.09202
Abstract
We present a prototype for a news search engine that presents balanced viewpoints across liberal and conservative articles with the goal of de-polarizing content and allowing users to escape their filter bubble. The balancing is done according to flexible user-defined constraints, and leverages recent advances in constrained bandit optimization. We showcase our balanced news feed by displaying it side-by-side with the news feed produced by a traditional (polarized) feed.
To appear as a demo-paper in IJCAI-ECAI 2018