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Rap History in Data

Whether you are a long-time dedicated hip-hop follower with a desire to study the trends of the social movement or a casual rap listener who wants to learn more about the genre (or anywhere inbetween), this article is for you to explore and to come up with your own observations and hypotheses. It's also a great way to find new music in the hip-hop genre that you might resonate with! With this article, I am not trying to argue any specific point about the nature/evolution of hip-hop; I am building onto the corpus of information that hip-hop scholars and normal Joe-Shmos can draw from to gain new knowledge and formulate their own arguments.

The data comes from Genius.com, the website where I webscraped the lyrics from. To do the webscraping, I used a python library called LyricsGenius. I cleaned and distilled the datapoints for the datavisualizations in python. Watch the video for more information on this. 

The website and the data visualizations themselves are made with the classic combination of HTML, CSS, and JS, with help from D3.js. To learn D3.js, I read a textbook called Fullstack D3 and Data Visualization by Amelia Wattenberger. 

This article allows you to explore lyrical trends in different rap subgenres like most common words, most influential artists, and most popular topics of each subgenre. the subgenres in the dataset include Old School, Golden Age, Gangsta, Crunk, Trap, Drill, and Mumble.




Anthony Pinter



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