Product rating using sentiment analysis
Customer feedbacks are the mile stones for the success functionality for the companies. A producer will get the correct result of his product from the customer feedback. He can make necessary changes to his product according to the feedback. But most users always fail to give their feedbacks. To avoid the difficulty of providing feedback, this paper focus on the technique of providing automatic feedback on the basis of data collected from Twitter. These data streams are filtered and analyzed and feedback is obtained through opinion mining. Here we mainly analyze the data for mobile phones. The experiments have shown 80% accuracy in the sentimental analysis. Our framework is able to provide fast, valuable feedbacks to companies.
2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)