Visualizing Networks of Music Artists with RAMA
Visualizing Networks of Music Artists with RAMA
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Date
2009
Authors
Luís Sarmento
Eugenio Oliveira
Fabien Gouyon
Bruno Costa
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Abstract
In this paper we present RAMA (Relational Artist MAps),
a simple yet efficient interface to navigate through
networks of music artists. RAMA is built upon a dataset of
artist similarity and user-defined tags regarding 583.000 artists
gathered from Last.fm. This third-party, publicly available, data
about artists similarity and artists tags is used to produce
a visualization of artists relations. RAMA provides two simultaneous
layers of information: (i) a graph built from artist similarity data,
and (ii) overlaid labels containing user-defined tags.
Differing from existing artist network visualization tools, the
proposed prototype emphasizes commonalities as well as
main differences between artist categorizations derived from
user-defined tags, hence providing enhanced browsing experiences to users.