A Methodological Survey on Sentiment Analysis Techniques and Their Applications in Opinion Mining

Opinion mining and sentiment analysis is a fast developing and growing research area.There are various e-commerce sites available on the net that provides choices to users to allow feedback regarding the specific product.This paper sharply focuses on survey of sentiment analysis techniques to check their effect on opinion mining.These feedbacks are significantly useful to both the people, who are willing to shop for that product and also the organizations.A correct technique for predicting sentiments may alter us, extract opinions from the web and predict customer's preferences.There are numerous algorithms available for opinion mining.Before applying any algorithmic rule for polarity detection, preprocessing on feedback is administered.From these pre-processed reviews opinion words and object on that opinion is generated are extracted and any opinion mining technique is applied to seek out the polarity of the review.Opinion mining has three levels of granularities: Document-level, Sentence level, and Aspect level.In this paper, numerous algorithms for sentiment analysis are studied and challenges and applications seem in this field are analyzed.