Analyzing the Impact of Filter Bubbles on Social Network Polarization

Abstract

While social networks have increased the diversity of ideas and information available to users, they are also blamed for increasing the polarization of user opinions. Eli Pariser's "filter bubble" hypothesis [55] explains this counterintuitive phenomenon by linking user polarization to algorithmic filtering: to increase user engagement, social media companies connect users with ideas they are already likely to agree with, thus creating echo chambers of users with very similar beliefs.