Today Twitter is generally the most common social media platform for an individual to express their views. Every minute hundreds of tweets are posted on the website of twitter related to many topics like politics, media, economy, education, health etc. Demonetization is one such topic, people from every other corner of the world tweeted their response and expressed their sentiments in good or bad way. From which some favoured demonetization while some opposed it. We can classify these tweets by using machine learning techniques. Also we can classify these tweets in positive, negative and neutral by using machine learning algorithm for sentiment analysis. For this purpose first pre-processing of data is done their after various existing algorithm like Hierarchical clustering, Support Vector Machine, Naïve Bayes, Logistic Regression is applied and then graph based visual model is presented for the better understanding of classification. Also the results of these techniques are compared and analysed on various parameters like correctness of algorithm, prediction and confusion matrix formation and then various conclusions are drawn. Copyright © 2019 American Scientific Publishers All rights reserved.