Sentiment Analysis of Reviews for E-Shopping Websites (International Journal of Engineering and Computer Science, 2017)
The sentiment analysis is one of the popular research area in the field of text mining. Internet has become very popular resource for information gathering. People can share their opinion related to any product, services, events etc over internet. Websites like Amazon, Snapdeal, Homeshop18 etc are popular sites where millions of users exchange their opinions and making it a valuable platform for tracking and analyzing opinion and sentiments. “What other people thing” is being an important piece of information whenever we want to take any decision. Sentiment analysis is the best solution. This gives important information for decision making in various domains. Various sentiment detection methods are available which affect the quality of result. In this paper we are finding the sentiments of people related to the services of E-shopping websites. The main goal is to compare the services of different E-shopping websites and analyzing which one is the best. For this we use five large dataset of five different E-shopping website which contains reviews related to the services. “Sentiwordnet dictionary” is used for finding scores of each word. Then sentiments are classified as negative, positive and neutral. It has been observed that the pre-processing of the data is greatly affecting the quality of detected sentiments. Finally analysis takes place based on classification.