Hip-Hop Misogyny Stats
What It Does
Hip-Hop Misogyny Stats is a database containing statistics on the use of misogynistic terms in popular hip-hop songs. At present, the database contains information on 222 different artists. Every time a user searches for an artist that is not in the database, that artist is added to the database. As such, there will be more entries in the database as more people use the site.
How it works
Hip-Hop Misogyny Stats collects its stats from RapGenius data, via this Ruby gem. When you search for an artist, it requests the lyrics for that artist's 20 most popular songs and then performs an analysis on those lyrics, counting the frequency of specific misogynistic terms. If the artist does not already exist in the database, the artist will then be added to the database. If there are fewer than 20 songs available from an artist, that artist will be added to the database but will not be displayed on the stats page, in the interest of providing a proper baseline for the stats.
It's worth noting that raw numbers don't tell the whole story: the stats you see on this site are provided without the surrounding context in which these lyrics exist. An artist with a higher score on this site is not necessarily more misogynistic than an artist with a lower score--the way in which words are used is often as important as the words themselves. These stats are provided as an educational resource, without judgement.
Why Hip Hop?
Since launching this project, a few people have asked me why I chose to single out hip-hop, as opposed to other genres of music. My primary reasons were as follows:
- A large amount of data on hip-hop songs was available in a machine-readable format, via RapGenius and Tim Roger’s RapGenius Ruby gem.
- Personally, I listen to a lot of hip-hop; a large part of my motivation in working on this project was to attempt to quantify my own exposure to casual misogyny through music.
- Misogyny in hip-hop often takes the form of commonly used terms and is therefore easier for a computer program to isolate and measure. The three terms counted in the database were specifically chosen because they are, arguably, inherently misogynistic words. That said, context is always important and in attempting to quantify, this data has completely divorced the lyrics it counts from any surrounding context.
I’m sensitive to the fact that hip-hop music and culture are often singled out for misogyny while casual misogyny in other genres is interrogated far less often. This project is intended as a proof-of-concept of the sort of analysis that can be done on RapGenius’ data and is largely the product of my own personal interest and the tools available to me. I hope that others will take this idea and/or codebase and apply it to other genres of music and bodies of text.
ShoutoutsBig shout to Tim Rogers; were it not for his RapGenius Ruby gem, this site would not be possible. Props to Brooks Swinnerton, who taught me a lot about Ruby and Rails. Respect to Allison Parrish, who sparked my interest in working with text and lyrics. Peace to the basedgods Johann Diedrick and Roopa Vasudevan for design feedback and testing help.
All of the stats and code for the site are made available for use under a Creative Commons Attribution License. The stats are available in JSON format via the API and the code for the site is available on GitHub.
Hip-Hop Misogyny Stats is not endorsed by or affiliated with Genius or RapGenius.com.