Visualizing Networks of Music Artists with RAMA

نویسندگان

  • Luís Sarmento
  • Fabien Gouyon
  • Bruno G. Costa
  • Eugénio C. Oliveira
چکیده

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.

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تاریخ انتشار 2009