Document details

Visualizing networks of music artists with RAMA

Author(s): Luís Sarmento ; Fabien Gouyon ; Bruno G. Costa ; Eugénio Oliveira

Date: 2009

Origin: Repositório Aberto da Universidade do Porto

Subject(s): Informática, Ciências da computação e da informação; Informatics, Computer and information sciences; Ciências exactas e naturais::Ciências da computação e da informação; Natural sciences::Computer and information sciences; Ciências exactas e naturais::Ciências da computação e da informação; Ciências exactas e naturais::Ciências da computação e da informação; Natural sciences::Computer and information sciences; Natural sciences::Computer and information sciences


Description

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.

In this paper we present RAMA (Relational Artist MAps), a simple yet efficient interface to navigate throughnetworks of music artists. RAMA is built upon a dataset of artist similarity and user-defined tags regarding583.000 artists gathered from Last.fm. This third-party, publicly available, data about artists similarity andartists tags is used to produce a visualization of artists relations. RAMA provides two simultaneous layers ofinformation: (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 commonalitiesas well as main differences between artist categorizations derived from user-defined tags, hence providingenhanced browsing experiences to users.

Document Type Book
Language English
Contributor(s) Faculdade de Engenharia
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