Identifying sociolinguistic attributes of inter-community interactions is essential for understanding the polarization of social network communities. A wide range of computational text and network analysis methods may be applicable for this task, however, interpretation of the respective results and investigation of particularly interesting cases and subnetworks are difficult due to the scale and complexity of the data, e.g., for the Reddit platform. In this poster paper, we present an interactive visual analysis interface that facilitates network exploration and comparison at different topological and multivariate attribute scales. Users are able to investigate text- and network-based properties of social network community interactions, identify anomalies of conflict starters, or gain insight into multivariate anomalies behind groups of negative social media posts.