Paper Title
Review of Sentiment Based Classification Techniques

Abstract
Electronic contents are increasing day by day as people are using different digital platforms in large scale. Such digital platforms of social media are convenient to provides freedom to express emotions about any individual, services, goods, and actions. Receiving feedback or reviews by the company for a product or service is an important factor to maintain the quality and service. Now in this digital era it is very easy to get such feedback through social media content of the users. The text content of user’s digital platform is used to detect the type of emotion through which it enhances the understanding of customers or users need. Digital content on the server increasing every second through different platforms. To identify this vast amount of data, researchers found great opportunity to analyze and find out the patterns of data. Many scholars work in the field of emotion mining through applying analytical algorithms to such large data. People have been working for decades in this field of text mining or sentiment classification, but still some of the issues that exist in the research sector that need to be addressed and resolved. In this paper, we have reviewed different research papers with their proposed sentiment classification techniques. Keywords - Text Mining, Opinion Mining, Micro Blog, Fuzziness, Precision, Accuracy, F-Measure