Politically biased moderation drives echo chamber formation: An analysis of user-driven content removals on Reddit

Abstract

Echo chambers - online spaces where individuals are met with reinforcing viewpoints and insulation from opposing viewpoints - are of increasing interest to social media platforms and policymakers amidst rising political polarization. Selective participation and algorithmic recommendations are commonly cited as drivers of echo chamber formation. In this work, we document a novel mechanism for the formation of echo chambers on social media sites: the politically biased content removal decisions of user moderators. Applying a combination of natural language processing and network analysis to characterize political leanings on a dataset of removed comments from 1.2 million users on Reddit, we document political bias in content removal: moderators are significantly more likely to remove content that differs from their political orientation. Further, using a matching approach, we show that content removals have an indirect chilling effect on censored users' subsequent political speech on the same channel. Finally, we conduct a counterfactual simulation and demonstrate that politically biased content removal increases echo chamber intensity. These findings are of broad interest to users, platforms and regulators who weigh the costs and benefits of freedom of expression with the logistics of moderating massive online spaces.

Keywords: Echo Chambers, Content Moderation, Social Media, Platform Governance, Political Bias, User Generated Content

JEL Classification: D83, D91