  In this article, a framework for defining and analysing a family of graphs or
networks from symbolic music information is discussed. Such graphs concern
different types of elements, such as pitches, chords and rhythms, and the
relations among them, and are built from quantitative or categorical data
contained in digital music scores. They are helpful in visualizing musical
features at once, thus leading to a computational tool for understanding the
general structural elements of a music fragment. Data obtained from a digital
score undergoes different analytical procedures from graph and network theory,
such as computing their centrality measures and entropy, and detecting their
communities. We analyze pieces of music coming from different styles, and
compare some of our results with conclusions from traditional music analysis
techniques.
