In recent years, polarization on social media has risen significantly. Social platforms often feature a range of topics that give rise to communities of users with diametrically opposed views, who tend to avoid engaging with others having different perspectives. We call these types of communities “diverging communities”. Examples include communities of supporters and skeptics of climate change or COVID-19 vaccines. In this paper, we aim to investigate this phenomenon. To do so, we first propose a formal definition of discording communities. We then present a framework for investigating the behavior of users of discording communities on a social platform. Our framework is general in that it can be adapted to any social platform where users discuss a topic that polarizes them into communities with diametrically opposed viewpoints rejecting confrontation. Our framework considers not only the structure of communities but also the content of the messages posted by their users. Finally, it can also handle the temporal evolution of the polarization level of both communities and their users. In addition to proposing a formal definition of diverging communities and presenting our framework, we illustrate the results of an extensive experimental campaign carried out on two case studies involving Reddit and X and show how our framework is able to identify a number of features that distinguish the users of one diverging community from the users of the other.
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