Sentiment analysis is an application of natural language processing. It is also known as emotion extraction or opinion
mining. It is a very popular field of research in text mining. The basic idea is to find the polarity of the text and classify it into
positive, negative or neutral. Polarity of text is determined from scores identified by VADER. It helps us to understand human
decision making or to categorize, analyze and extract opinions from review documents on web sites, blogs, social media, and
others in order to understand the consumers. To perform sentiment analysis, there are various algorithms such as SVM, Naïve
Bayes and DAN2 which are used to predict the polarities and find their accuracies. There are various tasks like subjectivity
detection, sentiment classification, aspect term extraction, feature extraction, keyword selection and keyword analysis etc. that
are needed to determine the polarity.
