Sentiment Analysis of Music using Statistics and Machine Learning
Authors:
Aakash Mukherjee and Soubhik Chakraborty
ISBN:
9788195293179
Binding:
Hardcover
Year:
2023
Pages:
84 with numerous colour and b/w figures, tables, and photos
Size:
15 x 23 x 1 cm
Weight:
257 grams
Price:
INR
595.00
Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.
Soubhik Chakraborty
Primarily a statistician, Soubhik Chakraborty is currently a Professor and formerly Head in the department of Mathematics, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India. His research interests are algorithm and music analysis involving extensive use of computational statistics. He has been guiding several research scholars leading to PhD in these areas and has published over 100 papers, 4 books and 7 research monographs. He is also an acknowledged reviewer associated with ACM, IEEE and AMS. Himself an amateur harmonium player and a former flutist, his recently published book Computational Musicology in Hindustani Music, joint with Prof. Guerino Mazzola (School of Music, University of Minnesota, USA) and Chakraborty’s own PhD scholars Dr Swarima Tewari and Dr Moujhuri Patra published by Springer in 2014 is the first book dedicated to the topic. He is also one of the authors of the book Signal Analysis of Hindustani Classical Music, Springer, 2017 jointly authored by Prof. Asoke Kumar Datta of Indian Statistical Institute, Kolkata and four other co-authors.
Swarima Tewari
A B.E. in Electrcal Engineering and an MTech. In Scientific Computing, Swarima Tewari has completed her PhD in the area of Computational Musicology, under the guidance of Prof. Soubhik Chakraborty, from Department of Mathematics, BIT Mesra, Ranchi, India. She is one of the authors of the book Computational Musicology in Hindustani Music published by Springer in 2014. She has the experience of working as a project fellow in a major research project titled Analyzing the Structure and Performance of Hindustani Classical Music through Statistics sponsored by the University Grants Commission with Prof. Soubhik Chakraborty as the principal investigator.
Arshi Rahman
Arshi Rahman completed her Integrated M.Sc. in Mathematics and Computing from Department of Mathematics, Birla Institute of Technology, Mesra, Ranchi, India. Currently she is employed in Price Waterhouse Coopers (PwC).
Maria Jamal
Maria Jamal completed her Integrated M.Sc. in Mathematics and Computing from Department of Mathematics, Birla Institute of Technology, Mesra, Ranchi, India. Currently she is employed in Byju’s Think and Learn Pvt. Ltd.
Apra Lipi
Apra Lipi completed her Integrated M.Sc. in Mathematics and Computing from Department of Mathematics, Birla Institute of Technology, Mesra, Ranchi. Currently she is a Guest faculty in Mathematics at Dr Shyama Prasad Mukherjee University in Ranchi, India.
Apoorva Chakraborty
Apoorva Chakraborty, an amateur Hindustani classical vocalist, is a Sangeet Visharad from Pracheen Kala Kendra, Chandigarh, India. She is also a certified music therapist from NADA Centre for Music Therapy, India. She is a student of Psychology (Hons) at Nalanda Open University. She has coauthored the award winning book Hindustani Classical Music: A Historical and Computational Study, Sanctum Books, 2021 with Prof. Soubhik Chakraborty.
Email: apoorvachakraborty2001@gmail.com
Affiliation: Nalanda Open University, Patna-800001, Bihar, India
Apoorva Nanda
Apoorva Nanda has completed her MTech in Computer Science from Department of Computer Science and Engineering, Birla institute of Technology, Mesra, Ranchi, India. Currently she is employed in Qualcomm India Pvt. Ltd.
Pranjala Shukla
Pranjala Shukla has completed her M.Tech in Computer Science from Department of Computer Science and Engineering, Birla institute of Technology, Mesra, Ranchi, India. Currently she is employed in Cloudcover Pvt Ltd (STT Telemedia). Previously she was employed in HCL Technologies Ltd. She has coauthored the award winning book Hindustani Classical Music: A Historical and Computational Study, Sanctum Books, 2021 with Prof. Soubhik Chakraborty.
Email: pranjala.shukla@gmail.com
Address: Department of Computer Science and Engineering, BIT
Mesra, Ranchi-835215, Jharkhand, India