Different Approaches of Sentiment Analysis - Supriya B, Moralwar; Sachin N, Deshmukh (International Journal of Computer Sciences and Engineering, 2015)
Sentiment analysis is a machine learning approach in which machines analyzes and classifies the sentiments, emotions, opinions about any particular topics or entity which are expressed in the form of text or speech. Due to large volume of textual data increasing on the web so much of the current research is focusing on the area of sentiment analysis. People are interested to develop and design a system that can identify and classify the sentiments as represented in textual form. Sentiment analysis is used to extract the subjective information in source material by applying various techniques such as Natural language Processing (NLP), Computational Linguistics and text analysis and classify the polarity of the opinion. In this paper, we are going to discuss different levels of sentiment analysis, approaches for sentiment classification, Data Source for sentiment analysis and comparative study of approaches for sentiment classification.