Roman Urdu Sentiment Analysis of Reviews on PSL Anthems

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.