Sentiment Analysis in E-commerce Using SVM on Roman Urdu Text

The usefulness and importance of sentiment analysis task is a widely discussed and effective technique in e-commerce. E-commerce is a very convenient way to buy things online. It saves a lot of time that is usually spent traveling and buying by visiting the shops. E-commerce provides an efficient and effective way to shop sitting right in front of one’s computer/mobile at home. For a given product, sentiment analysis captures the users views; their feelings and opinion related to that product. The reviews are categorized into three basic classes i.e. negative, positive, and neutral. This paper focuses on Urdu Roman reviews that are obtained by one of the most famous and accessed e-commerce website of Pakistan–Daraz.pk. There are total 20.286 K reviews which are annotated into three classes by three different experts. Vector space model, a.k.a bag of word model is applied for feature extraction which are later passed to Support Vector Machines (SVM) for sentiment classification. Experiments are conducted on MATLAB Linux server. The dataset is kept public for future use and experiments.