Sentiment Analysis for Roman Urdu
Journal: Mehran University Research Journal of Engineering and Technology (Vol.38, No. 2)Publication Date: 2019-04-01
Authors : Ayesha Rafique; Kamran Malik; Zubair Nawaz; Faisal Bukhari; Akhtar Hussain Jalbani;
Page : 463-470
Keywords : Roman Urdu; Sentiment Analysis; Feature Selection; Machine Learning Classifiers;
Abstract
The majority of online comments/opinions are written in text-free format. Sentiment Analysis can be used as a measure to express the polarity (positive/negative) of comments/opinions. These comments/ opinions can be in different languages i.e. English, Urdu, Roman Urdu, Hindi, Arabic etc. Mostly, people have worked on the sentiment analysis of the English language. Very limited research work has been done in Urdu or Roman Urdu languages. Whereas, Hindi/Urdu is the third largest language in the world. In this paper, we focus on the sentiment analysis of comments/opinions in Roman Urdu. There is no publicly available Roman Urdu public opinion dataset. We prepare a dataset by taking comments/opinions of people in Roman Urdu from different websites. Three supervised machine learning algorithms namely NB (Naive Bayes), LRSGD (Logistic Regression with Stochastic Gradient Descent) and SVM (Support Vector Machine) have been applied on this dataset. From results of experiments, it can be concluded that SVM performs better than NB and LRSGD in terms of accuracy. In case of SVM, an accuracy of 87.22% is achieved.
Other Latest Articles
- Feasibility and Optimization of Standalone PV/Biogas Hybrid Distributed Renewable System for Rural Electrification: A Case Study of a Cholistan Community
- A Multi Criteria Approach to Rank Renewable Energy Technologies for Domestic Sector Electricity Demand of Pakistan
- PREVALANCE AND MOLECULAR CHARACTERIZATION OF GIARDIA DUODENALIS IN LIVESTOCK IN VAN, TURKEY
- SUSTAINABLE TRANSPORT: AUSTRIA’S EXPERIENCE
- Managerial accounting: as it has to be
Last modified: 2019-05-14 14:12:56