Exploring community structure of sample-based music through bipartite network analysis

Abstract

Musical sampling is a popular music composition that takes part of an existing recording and uses it to create a new recording. In sample-based music, musical similarity can be claimed for two artists who sampled the same song. To derive a community based on this similarity, we created an artist-song bipartite network consisting of artists who are the subjects of sampling and songs that are the target of sampling and analyzed its community structure. This derived community can be understood as a single musical style, so this paper enhances our understanding of the stylistic aspects of sample-based music.