  Community structures detection in signed network is very important for
understanding not only the topology structures of signed networks, but also the
functions of them, such as information diffusion, epidemic spreading, etc. In
this paper, we develop a joint nonnegative matrix factorization model to detect
community structures. In addition, we propose modified partition density to
evaluate the quality of community structures. We use it to determine the
appropriate number of communities. The effectiveness of our approach is
demonstrated based on both synthetic and real-world networks.
