Abstract Sentiment Analysis is the way of categorizing the opinions and understanding the emotions expressed in the piece of text computationally. Recent researches involve the use of sentiment Analysis in various applications like multilingual webtexts, movie reviews, twitter dataset, etc. The various Machine learning techniques involve SVM, Random forest, Naive Bayes algorithm, and Lexical Analysis out of which SVM has the best accuracy but takes more time in training for the large and noisy dataset. Introducing sentiment analysis in the student feedback is an attempt to decrease the time taken to evaluate the feedbacks given by the students. Thus until now, in student feedback analysis, the feedback analysis is done where sentiment scores are assigned to feedback comments. Thus the sentiment score is converted in terms of rating. This paper has given brief review on student feedback analysis using sentiment analysis. This review explored that there are few problems which are not yet addressed by recent research like , there is a need for a system that will not only show the feedback as a rating but also be able to figure out the different parameters where the staff needs to improvise with help of graphical representations.Keywords: sentiment; SVM: Lexicon based approach; feedback; emotion