R.A.P. - Rap Analysis Project

As a capstone project for the MIDS program at the University of California, Berkeley, our team applied machine learning techniques and data science principles to a database of rap lyrics from 1980 to 2015. After an active exploration of the data, we chose to focus our efforts on ‘hit prediction’, particularly on what it takes to make it onto the weekly Billboard Top 100 charts. Through a combination of lyric features and the support vector machine (SVM) model, we were able to obtain over 70% accuracy in the prediction of past songs on the Billboard Top 100 chart.

Our website will give you insight into how we built the prediction system, the features used to power our model, and an opportunity to use the system to classify contemporary rap lyrics that you provide.

Link to website: http://bit.ly/rap_analysis