Comparing Echo Chamber Detection Metrics: A Cross-modeling and Cross-platform Analysis of Twitter and Reddit

Social media platforms have become central arenas for public discourse, enabling the exchange of ideas and information among diverse user groups. However, the rise of echo chambers, where individuals reinforce their existing beliefs through repeated interactions with like-minded users, poses significant challenges to the democratic exchange of ideas and the potential for polarization and information disorder. This paper presents a comparative analysis of the main metrics that have been proposed in the literature for echo chamber detection, with a focus on their application in a cross-platform scenario constituted by the two major social media platforms, i.e., Twitter (now renamed \(\mathbb {X} \) ) and Reddit. The echo chamber detection metrics considered encompass network analysis, content analysis, and hybrid solutions. The findings of this work shed light on the unique dynamics of echo chambers present on the two social media platforms, while also highlighting the strengths and limitations of various metrics employed to identify them, and their transversality to the different social graph modeling and domains considered.