The Social Network of Contemporary Popular Musicians

Abstract

In this paper, we analyze two social network datasets of contemporary musicians constructed from allmusic.com (AMG), a music and artists' information database: one is the collaboration network in which two musicians are connected if they have performed or produced an album together, and the other is the similarity network in which they are connected if they were musically similar according to the music experts. We find that, while both networks exhibit typical features of social networks such as high transitivity (clustering), we find that they differ significantly in some key network features such as the degree and the betweenness distributions. We believe that this highlights the fundamental differences in the construction mechanism (self-organized collaboration and human-perceived similarity) of the new networks.

Analyzing and modeling real-world phenomena with complex networks: a survey of applications

“…Another collaborative network was built by Park et al [343] who used data extracted from the allmusic.com database. They constructed a network of similarity between artists in this database and investigated the topological properties of both networks, in addition to the resulting networks obtained when intersecting them, i.e.…”

Analysis and Exploitation of Musician Social Networks for Recommendation and Discovery

“…All MFCCs are created with the fftExtract tool 12 . For each artist node a GMM is built from the concatenation of MFCC frames for all songs found on each artist's Myspace page.…”

“…These networks of musicians exhibit many of the properties expected in social networks [10]- [12]. However, these studies all examine networks created by experts (e.g.…”

Community Structure in Audio Clip Sharing

“…Network theory has also been extensively applied to music recommendation [2], [3]. In [4], communities of music listeners with similar tastes are found through modularity optimization.…”