Why is this research useful?
Literature Review
We are all aware that popular music has evolved through time. The number-one hit song in 2019 sounds very different to the number-one hit song in 1970. However, little research has been conducted to metrically assess how music has changed throughout the years - popular songs are often only classified by genre, limiting the scope of comparison.
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Some current studies have tried to address the lack of research in this niche. They suggest that the evolution of music is characterised by the rise and trends of pop songs (Lee Lin, 2012). The current applicable literature does put effort into delving and analysing songs, like the beats per minute of a track. However, it lacks the specific analysis of the composition of songs and their characteristics. The research does not evaluate the specific changes songs have undergone over time resulting in a 'smoother' evolution than it truly is.
This is where our research comes in. We aim to tackle this gap by providing an analysis of the audio features that make up the US Billboard Top 20 songs across the last 50 years. These audio features are derived from Spotify itself and include song length, danceability, energy, instrumentalness, acousticness, liveness, loudness, speechiness, tempo and time signature. By analysing these specific audio features, we will better understand what specifically makes a song popular, whether it is a mix of features or a leading feature, and the way they have evolved to form patterns throughout the years
Our Motivations
This research will have far reaching positive effects for music producers and potentially even consumers. Our research will be able to explain the actual makeup for popular songs throughout the years. Producers will be able to use this research to help shape their songs to become popular. Our data allows producers to analyse recent trends as well as retro trends to produce songs. They can even use our recent data to aid predictions of the audio features of popular songs in the coming years.
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Our data can also be used as a tool in conjunction with other research which has detailed analysis of surrounding factors, such as societal conditions, to make more accurate predictions. It can also be used to comment on society and can explore some societal behavioural norms. This is notably possible because of the expansive breakdown of Spotify’s audio features which goes further than the typical breakdown of length and artist but even explains features such as danceability, a crucial factor when understanding popular songs.
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Consumers may even be interested to view this information to understand more about their tastes and preferences which can serve as a form of self-introspection.
