Sentiment Analysis and Machine Learning Based Sentiment Classification: A Review

Abstract

Sentiments are the feelings expressed by an individual about entities such as products, services, organizations, individuals, issues, events, topics, and their attributes. Understanding the meaning of sentiment and interpreting them in positive, negative and neutral classes in a automated way is known as Sentiment Analysis. Machine Learning Classifier algorithms are used to classify the sentiment in different classes. This paper presents a comprehensive review of sentiment analysis addressing different concepts in this area, challenges applications along with a list of research areas in this field. It also addresses major machine learning algorithms used for sentiment classification, their comparisons and recent research work in this area.

Keywords : Opinion, Sentiment Analysis; Naïve Bayes ; Maximum Entropy; Decision Tree; Support Vector Machine.