International Journal of Innovative Research in Computer Science and Technology
Year: 2025, Volume: 13, Issue: 4
First page : ( 68) Last page : ( 75)
Online ISSN : 2347-5552
DOI: 10.55524/ijircst.2025.13.4.7 |
DOI URL: https://doi.org/10.55524/ijircst.2025.13.4.7
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)http://creativecommons.org/licenses/by/4.0
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Shilpa R , Sahana Kumari B, G C Divya
With the growing influence of social media, understanding user sentiments has become very important for various applications. The aim of this paper is to analyze sentiments in social media posts to detect whether they are positive, negative, or neutral and to provide a unique solution by suggesting music that aligns with the identified sentiment. The proposed system leverages Natural Language Processing (NLP) techniques and Logistic Regression for sentiment classification. The data is obtained from Twitter, where the posts are processed to extract meaningful insights. A web application has been developed using Python, HTML, and CSS to demonstrate the functionality of the model. The application not only predicts the sentiment of the given text but also suggests songs that suit the emotional state of the user, thereby improving the user experience. This paper demonstrates how sentiment analysis can be creatively integrated in daily life to make interactions more engaging and personalized.
Assistant Professor, CSE, SDMIT, Ujire, India
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