An End-to-End Toolkit for Social Network Analysis

Today's online social networks produce a significant amount of data containing rich information. A major challenge is to analyze and make sense of the data, so that useful information can be retrieved efficiently. In many application scenarios, this requires analyzing both the network topology and the textual information contained in the network. However, existing network analysis tools usually focus on one of these aspects, instead of providing end-to-end solutions for this particular research scenario. In this paper, we present NetNet, a social network analysis tool that is specifically designed to simplify the workflow of analyzing social networks. In NetNet, we model social networks as interconnected user nodes with text nodes associated with them, and leverage network analysis and text mining algorithms to perform both tasks seamlessly. We evaluate the performance of NetNet using social network data, and the experimental results show that our design is practically efficient and scalable.