Sentimental analysis using fuzzy and naive bayes

Abstract

Sentimental Analysis is the best way to judge people's opinion regarding a particular post. In this paper we present analysis for sentiment behavior of Twitter data. The proposed work utilizes the naive Bayes and fuzzy Classifier to classify Tweets into positive, negative or neural behavior of a particular person. We present experimental evaluation of our dataset and classification results which proved that combined proposed method is more efficient in terms of Accuracy, Precision and Recall.