It turns out there are actually a few hip-hop heads in the ranks of Daily Banter readership, as demonstrated by some pretty amazing discussions going on in the comment section of a piece I did last week on Questlove’s essay “How Hip-Hop Failed Black America,” so while this news may not have the same sociological gravitas as Quest’s piece, it’s noteworthy to at least a dedicated few on this site…
Aesop Rock has the best vocabulary of any rapper out there.
Well, he at least has the highest number of unique words used within his first 35,000 lyrics.
And we know this thanks to someone named Matt Daniels, whose byline awesomely reads: Matt Daniels is a designer, coder, and data scientist at Undercurrent in New York City. His past works include the Etymology of “Shorty” and Outkast, in graphs and charts.
Matt, in an act that can only be seen as a selfless gift to mankind, took the first 35,000 words of a slew of artists’ material (unfortuantely Biggie and Kendrick Lamar didn’t make the minimum cut) and analyzed that data for its lyrical diversity. He also included Shakespeare and Herman Melville as data point benchmarks…
You can check out more of the data over at his site (and you should), but more importantly, not content to just let his data float the web unanalyzed, Data Visualization Nerd Matt took off his hat and Hip-Hop Nerd Matt put his on (probably backwards) and highlighted some of the more interesting trends while throwing down knowledge on esoteric topics like E-40’s Shakespearean knack for word innovation and crunk music’s call-and-response structure.
It was quite a display of hip-hop acumen.
And again, I know most of you don’t care, but some of us do, and while this fine piece of data visualization and analysis will be but a ripple in the infinity pool of the internet, in the eyes of a few nerds (shoutout to JozefAL, CL Nicholson, Eric Cochran, and Jason E), Matt Daniels might have won the internet today.
(yes I have already reached out to Matt via Twitter about seeing a word-cloud of this data #datavizporn).