Genetic Data Tools Reveal How Pop Music Evolved In The US
By: The Physics Arxiv Blog
Tags: Culture, Music, Data Visualization

The history of pop music is rich in details, anecdotes, folk lore. And controversy. There is no shortage of debate over questions about the origin and influence of particular bands and musical styles.

But despite the keen interest in the evolution of pop music, there is little to back up most claims in the form of hard analytical evidence.

Today that changes thanks to the work of Matthias Mauch at Queen Mary University of London and a few pals who have used the number crunching techniques developed to understand genomic data to study the evolution of American pop music. These guys say they have found an objective way to categorise musical styles and to measure the way these styles change in popularity over time.

The team started with the complete list of US chart topping songs in the form of the US Billboard Hot 100 from 1960 to 2010. To analyse the music itself, they used 30-second segments of more than 80 per cent of these singles — a total of more than 17,000 songs.

They then analysed each segment for harmonic features such as chord changes and for the quality of timbre, whether guitar or piano or orchestra based, for example. In total, they rated each song in one of 8 different harmonic categories and one of 8 different timbre categories.

Mauch and co assumed that the specific combination of harmonic and timbre qualities determines the genre of music, whether rock, rap, country and so on. However, the standard definitions of music genres also capture non-musical features such as the age and ethnicity of the performers, as in classic rock or Korean pop and so on.

So the team used an algorithmic technique for finding clusters within networks of data to find objective categories of musical genre that depend only on the musical qualities. This technique threw up 13 separate styles of music.

An interesting question is what these styles represent. To find out, the team analysed the tags associated with each song on the Last-FM music discovery service. Using a technique from bioinformatics called enrichment analysis, they searched for tags that were more commonly associated with songs in each music style and then assumed that these gave a sense of the musical genres involved.

For example, they found that style 1 was associated with soul tags, style 2 with hip hop, style 3 with country music and easy listening, style 4 with jazz and blues and so on.

Finally, they plotted the popularity of each style over time.

The results make for fascinating reading. They found that the frequency of style 4 (jazz, blues etc) declined from 1960 onwards. Styles 5 and 13, which relate to rock music, fluctuate throughout this time. And style 2 (rap) is rare before 1980 but expands rapidly after that and becomes the dominant genre for the next 30 years before declining in the late 2000s.

The data allows them to settle some long standing debates among connoisseurs of popular music. One question is whether various practices in the music industry have led to a decline in the cultural variety of new music.

To study this issue, Mauch and co developed several measures of diversity and tracked how they changed over time. “We found that although all four evolve, two — diversity and disparity — show the most striking changes, both declining to a minimum around 1984, but then rebounding and increasing to a maximum in the early 2000s,” they say. Beyond that, their conclusion was clear. “We find no evidence for the progressive homogenisation of music in the charts,” they say.

Instead, they say that the evolution of music between 1960 and 2010 was largely constant but punctuated by periods of rapid change. “We identified three revolutions: a major one around 1991 and two smaller ones around 1964 and 1983,” they say.

The characters of these revolutions were all different with the 1964 revolution being the most complex. This consisted of an increase in popularity of styles 1, 5, 8, 12 and 13 which were enriched at the time for soul and rock-related tags. At the same time, styles 3 and 6 declined, enriched for tags such as doowop.

The 1983 revolution is associated with an increase in popularity of songs with tags such as new wave, disco and hard rock and a decline in soft rock and country tags.

The 1991 revolution is associated with the rise of rap-related tags.

Another question hotly debated by music commentators is how British bands such as the Beatles and The Rolling Stones influenced the American music scene in the early 1960s. Mauch and co are emphatic in their conclusion. “The British did not start the American revolution of 1964,” they say.

The team say the data clearly shows the revolution underway before The Beatles arrived in the States in 1964. However, British bands certainly rode the wave and played an important part in the way the revolution occurred.

That’s fascinating work. Because musicians copy, repeat and modify song styles they like, this leads to a clear pattern of evolution over time. So it should come as no surprise that techniques developed for the analysis of genetic data should work on music data as well. “The selective forces acting upon new songs are at least partly captured by their rise and fall through the ranks of the charts,” they say.

And there is much work to be done. Mauch and co point out that these number crunching techniques are quit general and so could be widely applied to cultural phenomenon, provided the data is available.

For the moment, they have their sights set on further music analysis. Their next task is to gather data going further back in time. “We are interested in extending the temporal range of our sample to at least the 1940s — if only to see whether 1955 was, as many have claimed, the birth date of Rock’n’Roll,” they say.

Worth waiting to find out!

Ref: arxiv.org/abs/1502.05417 : The Evolution of Popular Music: USA 1960–2010