Systematic Review on Machine Learning Approaches for Sentiment Analysis

Abstract

We live in the era of social media where millions of people use social media to express their
thoughts. To study those thoghts to gat the relvant information is Sentiment Analysis. Social media
works as a vast dataset which provide huge amount of blogs, tweets, comments and reviews. Data
mining and Machine Learning are two fields by which this data can be formed in decision and
prediction. In this paper, we are going to compare different methods of Machine learning approach
to estimate that which method provides more accuracy. These methods are Naïve Bayes, CART or
Decision tree, SVM and K Nearest Neighborclassifiers. Procedure of all these methods is different.
Objective of this paper to identify most efficient classification technique.