Echo Chambers in Collaborative Filtering Based Recommendation Systems

Understand

Recommendation systems underpin the serving of nearly all online content in the modern age.

• From Youtube and Netflix recommendations, to Facebook feeds and Google searches, these systems are designed to filter content to the predicted preferences of users.
• Recently, these systems have faced growing criticism with respect to their impact on content diversity, social polarization, and the health of public discourse.
• In this work we simulate the recommendations given by collaborative filtering algorithms on users in the MovieLens data set.