Billboard has kept a chart of their top 100 musicians since July 19, 2014, and like any of Billboard’s charts/lists/etc., the “Artist 100” attempts to measure, sanction, and archive the popularity or success of contemporary music in real time. Unfortunately, I can’t find any sort of announcement from Billboard outlining why the company instituted this new chart when it did, or what sorts of justification they used, and there’s no Billboard magazine from July 19, 2014, nor the week prior. An obvious difference between the Artist 100 and any of Billboard’s other charts is its focus on the musician rather than on a song or album.
The attempt to capture a musician‘s popularity as a sort of default, aggregate measure of success, comes at a somewhat crucial time for popular music’s consumption and distribution, at the initial steep curve in streaming’s rising ubiquity. Spotify, for instance, doubled its paid user-base (from 10 to 20 million) during the year from May 2014-May 2015, which has now ballooned to over 100 million. Two years later, Chance the Rapper became the first “streaming only” artist to win a Grammy. I’m sure someone has (or has had) something smart to say about the Artist 100 chart as a Thing, so I’d love if someone could point me towards that. If not, then someone should write something about it…
So, as a way to dust off the cobwebs after my first year of full-time teaching, I wanted to do some initial probing to see if I could find anything interesting about trends in how different musicians do on the chart. I didn’t really have any research questions in mind besides wondering if I could just make an easily accessible, well formed, informative dataset of the complete Artist 100 charts. My previous attempts at analyzing Billboard charts were an interesting exercise, but my dataset ended up messy, difficult to graph, and full of minor errors. My friend pointed me to some resources on “tidy” data organization practices, and I decided to try them out.
Long story short, I used Python packages for billboard and spotify APIs to scrape all rank data from the Artist 100 charts and then add genre labels that Spotify currently affixes to each musician. I’ve attached that dataset as a CSV file here. Check it out, play around, let me know if you find anything useful. I need to figure out how to automatically update this each week as a new chart is released.
As a little preview, I posted a basic graph on Tableau that tracks all of the artists who appear on the chart at least 5 times. It initially looks like a mess since it’s saturated with info. You can select artists by name from the column on the right to view individual graphs, or just click on the main plot itself. I’ve given a few that I found interesting below. I’d like to eventually do some work with this dataset on any trends in genre, chart ranking, artist demographic, time of year, etc.