Music Stream Analysis for the Prediction of Song Popularity using Machine Learning and Deep Learning Approach

Abstract

Music streaming services have increased in popularity due to ubiquitous demand of web and smart devices. Music lovers are inclined towards a variety of music styles and leave a different digital trail. The emotional responses that music can evoke in its listeners can result in both physiological adjustment and cognitive benefits. The world’s largest streaming service, Spotify, is the subject of this research. In this study, a model to predict whether a music would be featured on Hit-50 list of Spotify charts. This study employs the plotly for exploratory data analysis, offer descriptive statistical analysis, and compare machine learning approach with deep learning approach utilising Spotify data of eight months. Further, the study also identified several important features and correlation between them.