The best-selling song in the UK in 1985 was Jennifer Rush’s The Power of Love. Thirty years later, it was Uptown Funk, by Mark Ronson, with Bruno Mars. From the soft-rock power ballad to the dance floor, these were two very different highs of the charts.
It is obviously difficult to take a sample of two songs and draw meaningful conclusions about the changes in popular music. But what about a sample of 500,000 songs? This is exactly what scientists at the University of California at Irvine did, to track the trends in the success of different types of songs between 1985 and 2015.
The researchers used the growing availability of large datasets, in this case the online music encyclopedias Musicbrainz and Acousticbrainz. They analyzed half a million songs released in the UK over that 30-year period and correlated chart success with the songs’ acoustic characteristics.
These are broken down into variables such as timbre, tone, dance, mood, and genre groups. The results suggest that there is a general trend of fewer happy songs and more sad songs, while at the same time there has been an increase in the number of dance songs. Yet while this type of “big data” study can reveal new information about the music people listen to, it’s also important to have a big picture of how they listen.
The idea of pop songs getting sadder and sadder makes the read interesting and the titles catchy. But categorizing songs as “happy” or “sad” also depends greatly on social context and interaction. Take the example of a song that topped the charts twice, 16 years apart, Queen’s Bohemian Rhapsody. It’s a complex production on many levels, not directly danceable and sung from the point of view of a nihilistic murderer for whom “nothing really matters”. Yet it is the source of a very happy group participation.
It should also be considered that the way we consume music, and how that consumption is measured, has changed a lot in 30 years. Ratings are much less important now that the amount of music available to the average listener is an order of magnitude greater than it was in 1985. At the time, audiences relied on a relatively small number of stations. to listen to new music. The charts were selected from a limited number of available singles and were much more important in people’s daily listening.
Today listeners have the history of recorded music in their pockets and increased control over how it is listed and ordered to taste. The technology we use to listen to music has even altered our relationship with it, simultaneously expanding the parameters of musical choice and making the listening experience more intensely private.
Even though the graphics themselves have adapted over the decades, incorporating downloads in 2004 and streaming in 2014, they don’t represent the same measure of cultural dominance as they once did. As psychologists Raymond MacDonald, David Hargreaves, and Dorothy Miell note, there has been a “democratization of musical styles to the extent that the earlier association of some styles with ‘serious’ and others with ‘popularity’ n ‘no longer exists to the same extent’.
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While the charts record mainstream success, they also interact with and are fueled by musical subcultures that are often set in opposition to that mainstream. They grow up primarily because they’re different from what’s on the charts, but can eventually be successful building on that status, creating tension with the original fans.
For example, once tabloid newspapers began to regularly use terms like “acid house” and feature smiley-faced t-shirts in their fashion selections, many original rave fans continued to maintain their sense of distance and opposition to the general public. It’s a pattern familiar with musical subcultures – from mods to hippies to punks – as their markers of difference fit into the larger cultural milieu.
Popular music is therefore a contested territory. Taste models are constantly evolving, with chart success being only one axis of the impact of music.
The limits of big data
The recommendation algorithms of big tech companies are increasingly a part of the musical and cultural choice process, and the massive data sets associated with them are a huge resource for researchers. But the “popular” in popular music is more than a simple quantitative measure of consumption, and it cannot be reduced to aesthetic and stylistic components. It is also necessary to take into account its social functions. And that means researchers from different disciplines – both artistic and scientific – engage in a dialogue to analyze and interpret the data.
Music encoded as digital data now feeds into the larger matrix of economic and political decision-making, such as the Bank of England using it to take economic temperatures. It is therefore more important than ever that the social aspect of music use is not buried under the numbers.
