In this study we present a network analysis of the communities of artists based on sampling relationships. We construct a bipartite network between the artists who perform the sampling and the samples, then detect communities of the artists and the samples. We find that sample-based music has a clear community structure where each community features artists (nodes) with high centralities, allowing us to determine its musical style.We also define and visualize the similarities between communities representing distinct generations to observe how sample-based musical styles have evolved or "handed off" to the posterity. This study not only enhances our understanding of sampling-based music, but also presents a novel application of network community structures to a creative enterprise such as music.