Tag Archives | signed networks

The influential “echo chamber” hypothesis suggests that social media drive polarization through a mutual reinforcement between isolation and radicalization. The existence of such echo chambers has been a central focus of academic debate, with competing studies finding ostensibly contradictory empirical evidence. This article identifies a fundamental methodological limitation of these empirical studies: they do not differentiate between negative and positive interactions. To overcome this limitation, we develop a method to extract signed network representations of Twitter/X debates using machine learning. Applying our approach to a major Dutch cultural controversy, we show that the inclusion of negative interactions provides a new empirical picture of the dynamics of online polarization. Our findings suggest that conflict, not isolation, is at the heart of polarization.

This work is licensed under a Creative Commons Attribution 4.0 International License.