Roman Urdu Sentiment Analysis of Reviews on PSL Anthems

Roman Urdu Sentiment Analysis of Reviews on Pakistan Super League Anthems

  • Muhammad Qureshi Bahria University Lahore Campus
  • Muhammad Asif Lahore Institute of Science and Technology, Lahore, Pakistan
  • Mujahid Bashir Dr Hasan Murad School of Management, University of Management and Technology, Lahore, Pakistan
  • Hafiz Muhammad Zain Dr Hasan Murad School of Management, University of Management and Technology, Lahore, Pakistan
  • Muhammad Shoaib 4Department of Physics and Astronomy, University of Bologna, Bologna, Italy
Keywords: Sentiment Analysis, Roman Urdu Sentiment Analysis, Natural Language Reviews, Machine Learning, PSL Reviews Analysis

Abstract

Due to the easy access of internet and smart devices, people are becoming habitual to give their feedback on what they hear or watch, online. These reviews are very valuable for all sorts of users. Due to the widespread online activities, the count of these reviews has raised tremendously. This fact makes it humanly impossible to analyse them manually. So it needs time that reviews to be analysed and use patterns to be found and explored through the automated channel. This led to a new field of research known as Sentiment Analysis. This paper is targeting to design a model to perform sentiment analysis of Roman Urdu text using the reviews of Pakistan Super League’s official song. To perform this analysis five different techniques-- Naïve Bayes Kernal, Random Forest, Logistic Regression, K-Nearest Neighbour and Artificial Neural Network, are applied. Naïve Bayes Kernal and Logistic Regression correctly predicted 97.00% reviews.

Author Biography

Muhammad Asif, Lahore Institute of Science and Technology, Lahore, Pakistan

Muhammad Asif received the M.S./M.Phil. degree in computer sciences from Bahria University Lahore Campus, Lahore, Pakistan. He is currently pursuing a PhD degree at the University of Bologna, Italy. As a reviewer, he is working with multiple journals, i.e., IEEE Access, Computers, Materials and Continua, Intelligent Automation and Soft Computing, and some others. His research interests include natural language processing, machine learning, artificial intelligence, data sciences, and big data.

Published
2022-08-01
How to Cite
Qureshi, M., Asif, M., Bashir, M., Zain, H. M., & Shoaib, M. (2022). Roman Urdu Sentiment Analysis of Reviews on PSL Anthems: Roman Urdu Sentiment Analysis of Reviews on Pakistan Super League Anthems. Lahore Garrison University Research Journal of Computer Science and Information Technology, 6(03), 12-19. https://doi.org/10.54692/lgurjcsit.2022.0603351
Section
Articles