EXPANDING THE APPLICABILITY OF SENTIMENT ANALYSIS FOR PAKISTANI PRODUCTS

Abstract

Urdu language is widely spoken around the world by almost 30 million people but still it is not given due attention. Also, it is used in areas where the broadband users are rapidly increasing. People in Pakistan tend to communicate their feelings towards an entity in Urdu, roman Urdu or English. There are several tools and techniques available for performing sentiment analysis but as the data is ever growing, the uncertainty in data is also growing. In this research, we have put our efforts to bring about a system that performs sentiment analysis on Urdu, Roman Urdu and English which are the three most widely used languages for comments on Pakistani products. In order to extract the sentiment expressed in the text we wanted to implement such a model that could handle comments or reviews written in all the three languages. People often write their comments in roman Urdu which is Urdu written in roman script. The challenge with roman Urdu is that it has no defined structure, lexicon or grammar. Thus, in order to process the comments we converted all the reviews and comments to English and then applied sentiment analysis models on it. We have used multiple classifiers which include Naïve Bayes, Random Forest and SVM for this purpose. At the end we have discussed the performance of the classifiers and it was concluded that SVM outperformed the rest of the classifiers.