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The music industry is a $130 billion industry. Predicting whether a songcatches the pulse of the audience impacts the industry. In this paper weanalyze language inside the lyrics of the songs using several computationallinguistic algorithms and predict whether a song would make to the top orbottom of the billboard rankings based on the language features. We trained andtested an SVM classifier with a radial kernel function on the linguisticfeatures. Results indicate that we can classify whether a song belongs to topand bottom of the billboard charts with a precision of 0.76.

Predicting the top and bottom ranks of billboard songs using Machine Learning