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Social media provides an essential platform for shaping and sharing opinionsand consuming information in a decentralized way. However, users often interactwith and are exposed to information mostly aligned with their beliefs, creatinga positive feedback mechanism that reinforces those beliefs and excludescontrasting ones. In this paper, we study such mechanisms by analyzing thesocial network dynamics of controversial Twitter discussions using unsupervisedmethods that demand little computational power. Specifically, we focus on theretweet networks of the climate change conversation during 2019, when importantclimate social movements flourished. We find echo chambers of climate believersand climate skeptics that we identify based solely on the retweeting patternsof Twitter users. In particular, we study the information sources, or chambers,consumed by the audience of the leading users of the conversation. Users withsimilar (contrasting) ideological positions show significantly high(low)-overlapping chambers, resulting in a bimodal overlap distribution.Further, we uncover the ideological position of previously unobservedhigh-impact users based on how many audience members fall into either echochamber. We uncover the ideology of more than half of the retweeting populationas either climate believers or skeptics and find that the cross-groupcommunication is small. Moreover, we find that, while the echo chamberstructures are consistent throughout the year, most users inside the echochambers change from one week to the next, suggesting that they are a stableemergent property of the Twittersphere. Interestingly, we detect a significantdecrease in polarization and a significant increase on the number of climateskeptics that coincides with the main #FridaysForFuture strikes duringSeptember, 2019.

Quantifying the structure of controversial discussions with unsupervised methods: a look into the Twitter climate change conversation