SURVEY ON DUAL IMPLEMENTATION IN SENTIMENT ANALYSIS

Abstract

Sentiment Analysis is one of the trending research topics on which people are working widely to enhance its effectiveness and availability. But still proposed methodologies are lagging when it comes to accuracy and the size of dataset. With the ongoing evolutions in the field of technology here I tried to emphasize the role of dual implementation in Sentiment Analysis Here we are working on the same to enhance the accuracy of the result set. Also, here we included the different domains in which sentiment analysis are implemented and there comparision with other different applications and the challenges faced in there which involves the data related, accuracy issues related challenges and other similar issues. We are also discussing about the methodologies they are using in their paper. But here we are mainly focused on improving the accuracy by applying multiple implementations on training data set like adding multiple attributes based on the type of issue, training same data set with different methodologies and by data manipulation. We are also comparing behavior of results of different cases using different classification methods so that we get a better understanding on type of issues and in return, accuracy on result set gets better.