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Sentiment Analysis of User on the basis of Listened Songs

by Umang Rastogi, Shubham Goel, Venkat Maan, Utkarsh Agarwal, Varchsva Arya, Ajay Kumar Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 35
Year of Publication: 2020
Authors: Umang Rastogi, Shubham Goel, Venkat Maan, Utkarsh Agarwal, Varchsva Arya, Ajay Kumar Singh
10.5120/ijca2020920425

Umang Rastogi, Shubham Goel, Venkat Maan, Utkarsh Agarwal, Varchsva Arya, Ajay Kumar Singh . Sentiment Analysis of User on the basis of Listened Songs. International Journal of Computer Applications. 176, 35 ( Jul 2020), 19-26. DOI=10.5120/ijca2020920425

@article{ 10.5120/ijca2020920425,
author = { Umang Rastogi, Shubham Goel, Venkat Maan, Utkarsh Agarwal, Varchsva Arya, Ajay Kumar Singh },
title = { Sentiment Analysis of User on the basis of Listened Songs },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2020 },
volume = { 176 },
number = { 35 },
month = { Jul },
year = { 2020 },
issn = { 0975-8887 },
pages = { 19-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number35/31426-2020920425/ },
doi = { 10.5120/ijca2020920425 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:44:14.775805+05:30
%A Umang Rastogi
%A Shubham Goel
%A Venkat Maan
%A Utkarsh Agarwal
%A Varchsva Arya
%A Ajay Kumar Singh
%T Sentiment Analysis of User on the basis of Listened Songs
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 35
%P 19-26
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an algorithm is proposed to detect the sentiments of the user who listen the song. This project can be used to perform emotional analysis of a person on the basis of songs /Music listened by him and that analysis can be further used to predict the sentiments and mood of that person. This application can be used by different websites to recommend the songs, music or videos on the basis of sentiments of users detected by this application.

References
  1. Apoorv Agarwal, Renu Dhir, Geeta Sikka, Vivek Sharma: Sentiments mining and classification of music lyrics using SentiWordNet, 2016 Symposium on Colossal Data Analysis and Networking (CDAN), IEEE, 2016.
  2. Mahesh Ahuja, A. L. Sangal, “Opinion mining and classification of music lyrics using supervised learning algorithms”, 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC).
  3. B. Logan, A. Kositsky and P. Moreno, "Semantic analysis of song lyrics", 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).
  4. V. Stratton and A. Zalanowski, "Affective Impact of Music vs. Lyrics", Empirical Studies of the Arts, vol. 12, no. 2, pp. 173-184, 1994.
  5. S. Oh, M. Hahn and J. Kim, "Music Mood Classification Using Intro and Refrain Parts of Lyrics", 2013 International Conference on Information Science and Applications (ICISA), 2013.
  6. Bing Liu., “Sentiment Analysis and Opinion Mining”, Morgan & Claypool Publishers.
  7. H. Binali, V. Potdar and C. Wu, "A state of the art opinion mining and its application domains", 2009 IEEE International Conference on Industrial Technology, 2009.
  8. Demóstenes Zegarra Rodríguez, Graça Bressan and Renata Lopes Rosa, “Music Recommendation System Based on User’s Sentiments Extracted from Social Networks” ,Department of Computer Science and Digital Systems – University of São Paulo São Paulo, Brazil.
  9. Saurabh Yadav and Ajay Kumar Singh, “A Biometric Traits Based Authentication System for Indian Voting System,” International Journal of Computer Application (IJCA), ISSN: 0975-8887, vol. 65, no.15, pp. 159-162, March 2013. doi: 10.5120/11002-6185.
  10. Sharu Goel and Ajay Kumar Singh, “QR Code Implementation in Photo I-Card for Photo and Text Credentials using .NET,” International Journal of Computer Applications, Innovations in Computing and Information Technology (Cognition 2015), ISSN:  0975-8887, pp. 20-24, August 2014.
  11. Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco, “A Practical Guide to Sentiment Analysis”, Springer International Publishing AG 2017.
Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Sentiment Detection Mood Minimum Sentiment Maximum Sentiment.

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