A General Definition of Network Communities and the Corresponding Detection Algorithm

Network structures, consisting of nodes and edges, have applications in almost all subjects. The sets of nodes strongly connected internally are called communities. Industries (including cell phone carriers and online social media companies) need community structures to allocate network resources and provide proper customer services. However, all community detection methods are motivated by solving some concrete problems, while the applicabilities in other fields are open to question. Therefore, confronting a new community problem, researchers need to derive algorithms ad hoc, which is timeconsuming and even unnecessary. In this paper, we represent a general procedure to find community structures in concrete problems. We mainly focus on two typical types of networks: transmission networks and similarity networks. We reduce them to a unified graph model, based on which we propose a general method to define and detect communities. Readers can specialize our general algorithm to accommodate their problems. In the end, we also give a demonstration to show how the algorithm works.