A Hybrid Approach To Music Recommendation Using Sentiment Analysis

Abstract

In today ’s fast - paced scenario, music systems allow quick access to huge volumes of content. They are always trying to enhance music organization and search management, dealing with the issue of choice and making it easier to discover new music pieces. Recommendation systems are becoming increasingly common, assisting consumers in selecting acceptable soundtracks for all times. But although, there seems to be a void in customization and suggestion based on mood of the end user. Music has a powerful impact on people and is extensively utilized for relaxation, mood control, stress relief, and illness prevention, as well as to sustain mental and physical work. The creation of a personalized recommendation system based on listener’s sentiments, moods, and activity settings will be proposed in this research paper. This recommendation system is being developed using the concept of sentiment analysis to assist people with music choices for everyday circumstances while also maintaining their mental and physical health.