Social media provides an essential platform for shaping and sharing opinions and consuming information in a decentralized way. However, users often interact with and are exposed to information mostly aligned with their beliefs, creating a positive feedback mechanism that reinforces those beliefs and excludes contrasting ones. In this paper, we study such mechanisms by analyzing the social network dynamics of controversial Twitter discussions using unsupervised methods that demand little computational power. Specifically, we focus on the retweet networks of the climate change conversation during 2019, when important climate social movements flourished. We find echo chambers of climate believers and climate skeptics that we identify based solely on the users retweeted by the audience (here referred to as the chamber ) associated with the leading users of the conversation. Users with similar (contrasting) ideological positions show significantly high (low)overlapping chambers, resulting in a bimodal overlap distribution. Further, we uncover the ideological position of previously unobserved high-impact users based on how many audience members fall into either echo chamber. We classify more than half of the retweeting population as either climate believers or skeptics and find that the cross-group communication is negligible. Moreover, we find that, while the echo chamber structures are consistent throughout the year, most users inside the echo chambers change from one week to the next, suggesting that they are a stable emergent property of the Twittersphere. Interestingly, we observe a high correlation between the main #FridaysForFuture strikes and the sizes of the climate skeptics' echo chambers but no significant correlation with those of the climate believers.
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