Text Classification on Customer Review Dataset Using Support Vector Machine

Customer review is constantly generated in the form of text based on customer opinion concerning specific products in the electronic (e)-commerce space. With the proliferation of data, the classification of customers' opinions is a major issue in e-commerce. However, merchants frequently require customers to input their opinion about a product, in order to harvest customer experiences. The text classification technique helps customers and merchants to know if a product has a positive or negative review. This will enable merchants to improve the customer experience and also improve the revenue of the company. Sentiment analysis was executed on a customer product review dataset using support vector machine (SVM) in this study. The experimental results obtained show an accuracy of 86.67% in classifying customers' opinions on selected products. The findings will guide merchants to know customer feedback and identify their needs to improve sales culminating in increased revenue.