MEASURING DISRUPTION IN SONG SIMILARITY NETWORKS Felipe Falcão1 Nazareno Andrade1 Flávio Figueiredo2 Diego Silva3 Fabio Morais1 1 Universidade Federal de Campina Grande, Brazil 2 Universidade Federal de Minas Gerais, Brazil 3 Universidade Federal de São Carlos, Brazil
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[email protected] ABSTRACT Investigating music with a focus on the similarity relations between songs, albums, and artists plays an important role when trying to understand trends in the history of music genres. In particular, representing these relations as a sim- ilarity network allows us to investigate the innovation pre- sented by these entities in a multitude of points-of-view, including disruption. A disruptive object is one that cre- ates a new stream of events, changing the traditional way of how a context usually works. The proper measurement of disruption remains as a task with large room for improve- ment, and these gaps are even more evident in the music Figure 1. Network topology for a disruptive artist. domain, where the topic has not received much attention so far. This work builds on preliminary studies focused on the analysis of music disruption derived from metadata- Regarding the different creative roles played by artists based similarity networks, demonstrating that the raw au- during the genre trajectories, the AllMusic guide defines dio can augment similarity information. We developed a the Ramones as “inarguably the most relevant band in case study based on a collection of a Brazilian local music punk history, creating the stylistic prototype that would tradition called Forró, that emphasizes the analytical and be followed by countless bands who emerged in their musicological potential of the musical disruption metric to wake” 1 .