The time of a song's release proved to be a valuable feature in our model. Rap music has clearly evolved over the past 30 years, and so a hit in the 2000s has different characterstics than a hit in the 1980s. The visualization below represents the emergence of rap music onto the weekly Billboard Top 100 charts, with the darker green squares representing a higher percentage of rap music in the top 100.
Using the Alchemy API, we were able to extract places that were referenced in each song in our dataset. The interactive map below illustrates the concentrations of geographic references in rap songs for the past 30 years.
The Alchemy API was flexible enough to allow us to create the following heatmap which visualizes songs that reference geographic locations as well as crimes.Interestingly, many places that experience high crime rates in real life, are often mentioned in songs describing criminal activity.
We used Mallet to determine the themes present in each song in our dataset. We first primed Mallet on a wikipedia dataset, and then applied it to our songs to better ensure clean output. In the visualizations below, you can view the top 20 most popular themes from 1980 to today.
There are a lot of references to brand names in rap music. The word cloud below visualizes the frequency of the different brands that were namechecked in the songs in our dataset.
Vulgarity in rap music is ubiquitous, and surprisingly, it's one of our most important features in our model. The use of the different swear words are visualized over time below. We've censored the chart, but it doesn't take too much of a leap to figure out what words we're referencing.