%0 Journal Article
%T Predicting the top and bottom ranks of billboard songs using Machine Learning
%A Vivek Datla
%A Abhinav Vishnu
%J Computer Science
%D 2015
%I arXiv
%X The music industry is a $130 billion industry. Predicting whether a song catches the pulse of the audience impacts the industry. In this paper we analyze language inside the lyrics of the songs using several computational linguistic algorithms and predict whether a song would make to the top or bottom of the billboard rankings based on the language features. We trained and tested an SVM classifier with a radial kernel function on the linguistic features. Results indicate that we can classify whether a song belongs to top and bottom of the billboard charts with a precision of 0.76.
%U http://arxiv.org/abs/1512.01283v1