Sentiment Analysis is the process of computationally identifying and categorizing opinions expressed in a piece of text, especially to determine whether the writer’s attitude towards a particular topic, product, etc. is positive, negative or neutral. Nowadays the growth of social media, websites, blogging services and electronic media contributes to a huge amount of users giving messages such as customer reviews, comments and opinions. Sentiment Analysis is an important term referred to collecting information from a source by using Natural language Processing (NLP), text analysis and computational linguistics to make decisions by subjective information extracting and analyzing opinion, identifying positive and negative reviews measuring how positively and negatively an entity (public, organization, and product) is involved. Sentiment Analysis is the area of study to analyze people’s reviews, emotions, attitudes and emotions from written languages. We concentrate on fields of different opinion classification techniques, performed on any dataset. Nowadays most popular approaches are the bag of words and feature extraction used by researchers to deal with Sentiment Analysis i.e. used by politicians, news groups, manufacturing organizations, movie reviews products etc.