The echoes from social media: modeling how filter bubbles and network structure shape echo chamber emergence

The extent of echo chambers in social media and their impact on polarization is an open debate in the political science literature. There is mixed evidence about the extent to which these opinion-reinforcement communities exist and contribute to polarization and the erosion of social cohesion. This paper employs a social simulation approach that draws on political communication and social influence theories to explain how echo chambers can emerge on social media platforms. The agent-based model developed here integrates individual social networks (online and offline) with opinion dynamics to untangle the respective roles of social media algorithms and social network structures. Simulation conditions separately manipulated (1) the homophily or group similarity in personal networks and (2) the level of selective exposure to confirming information through filter bubbles on social media. We found that individuals’ information exposure significantly influenced echo chamber emergence, particularly in initially random social networks where people are surrounded by a diverse group of others. At the same time, artificially creating echo chambers did not ensure their persistence over time in the presence of filtering algorithms. Overall, we need to reconsider how we understand echo chambers and the mechanisms responsible for this phenomenon.