Instrumentational Complexity of Music Genres and Why Simplicity Sells

Abstract

Listening habits are strongly influenced by two opposing aspects, the desire for variety and the demand for uniformity in music. In this work we quantify these two notions in terms of instrumentation and production technologies that are typically involved in crafting popular music. We assign an ‘instrumentational complexity value’ to each music style. Styles of low instrumentational complexity tend to have generic instrumentations that can also be found in many other styles. Styles of high complexity, on the other hand, are characterized by a large variety of instruments that can only be found in a small number of other styles. To model these results we propose a simple stochastic model that explicitly takes the capabilities of artists into account. We find empirical evidence that individual styles show dramatic changes in their instrumentational complexity over the last fifty years. ‘New wave’ or ‘disco’ quickly climbed towards higher complexity in the 70s and fell back to low complexity levels shortly afterwards, whereas styles like ‘folk rock’ remained at constant high instrumentational complexity levels. We show that changes in the instrumentational complexity of a style are related to its number of sales and to the number of artists contributing to that style. As a style attracts a growing number of artists, its instrumentational variety usually increases. At the same time the instrumentational uniformity of a style decreases, i.e. a unique stylistic and increasingly complex expression pattern emerges. In contrast, album sales of a given style typically increase with decreasing instrumentational complexity. This can be interpreted as music becoming increasingly formulaic in terms of instrumentation once commercial or mainstream success sets in.

Product proliferation, complexity, and deterrence to imitation in differentiated‐product oligopolies

“…Kennedy, 2002), changes in their pattern of behavior are easier to observe empirically. Finally, this setting suits our purpose because the various regions or subspaces whereby the market for recorded music is partitioned-that is, genres and subgenres-can differ greatly in complexity (Percino, Klimek, & Thurner, 2014).…”

Decomposing Complexity Preferences for Music

“…The genres of the 25 stimulus songs were as follows: rock-n-roll, adult contemporary, electronica, soft rock, europop, R&B soul, rap, avant-garde classical, classical, latin, traditional jazz, world beat, classic rock, heavy metal, punk, bluegrass, mainstream country, new country. Since different genres tend to have different instrumental complexity levels (Percino et al, 2014), this variety serves to diversify the levels of complexity in the dataset. A full list of the songs in order of increasing complexity is available in Supplementary Materials.…”

“…These dimensions or factors cover properties such as frequency and/or number of events, harmony and syncopation, variability, and number of instruments. Often the definitions of music complexity adopted in different studies have focused on only one of these properties, e.g., rhythm and meter complexity (Shmulevich and Povel, 2000; Thul and Toussaint, 2008; Vuust and Witek, 2014), instrumental complexity (Percino et al, 2014), tonal complexity (Weiss and Muller, 2015), and harmonic complexity (Marsik et al, 2014). Few other studies took an integrated approach by combining multiple music properties (Streich, 2007; Mauch and Levy, 2011; Marin and Leder, 2013).…”

Digital Musical Instruments as Probes: How computation changes the mode-of-being of musical instruments

“…The 16-step paradigms of electronic sequencers and drum-machines, or the 4/4 time signature and 120 beats-per-minute setups of most DAWs, implicitly direct the way we conceive of music-making in ways that acoustic instruments never did. The result is that music has become more homogeneous and standardised, following a technological normatisation in composition, performance and mixing-mastering techniques (Percino, Klimek and Thurner 2014).…”