Cover versions as an impact indicator in popular music: A quantitative network analysis

Abstract

In contemporary popular music, covering or adapting previous songs signals a tribute or reworking of popular hits, which implies acknowledgement of the original musicians. This connection can be interpreted as a form of musical impact among artists. A network graph with more than 106k artists and 855k cover versions extracted from the web site SecondHandSongs was created. The objective is to explore the shape of this network, identify the most relevant artists according to different impact measurements and to visualize connections between music genres. This analysis is done from a longitudinal perspective with the aim of understanding how cover versions can inform us about the history of the contemporary popular music. Results show that the number of covers by artist is skewed distributed, diminishing gradually since the 1950s. Different network metrics have allowed to identify the most covered (weighted indegree), the most influential (PageRank) and the most crossover artists (weighted betweenness centrality). The network graph also shows that genre affinity is the main criterion for covering songs between artists, language being the second. Remakes from other genres reflect that Jazz and Pop/Rock are the most influential because they emerge stronger and form the core of their respective sub-networks. Cover songs describe two cycles. In a first phase from 1900s to 1950s, dominated by Jazz and Vocal artists, the covers are more frequent and associated with the notion of reworking (e.g. jazz standards); in a second stage, since the 1950s, when the Pop/Rock emerges, cover songs are less common and seen as tribute.

Fig 1. Cumulative distribution function (CDF) of the number of received (indegree) and performed (outdegree) covers by artist (log-log), and their respective exponents (α).

Fig 2. Evolution of the weighted average degree and clustering coefficient over the decades.

Fig 3. Heat map with the percentage of covers performed by artists that started their career in certain decade (x) to artists from other decades (y).

Fig 4. Evolution of the number of covered songs (weighted indegree) of the first ten artists in each decade.

Fig 5. Evolution of the PageRank of the first ten artists in each decade.

Fig 6. Directed network graph of artists (N = 106,095) linked through covers (N = 855,650), coloured according to music genre, with node size according to number of recorded songs (Layout = Fruchterman Reingold).

Fig 7. Cover flows between music genres (N = 35) (arcs≥10% of outdegree) (Layout = Yifan Hu).

Fig 8. Heat map with the percentage of covered music genres by decade.