Demonetization(500&1000):Analysis of Sentiments using NLTK Withtwitter for Text and Image

The main objective of our research is to analyse sentiments on the activity that happened in 2016, named as demonetization. In our research we have collected data by using twitter API. Twitter Application provides four unique tokens i.e. consumer key, consumer Secret, access token, access secret. These keys are unique to every user and comes with certain constraints. After collecting tweets from twitter, preprocessing is performed i.e. removal of stop words like removing punctuations, hash tags etc. After that, by using NLTK we classified the tweets into positive, negative and neutral. In the end tweets are classified by using Kmeans clustering also. In the end, we finally came to a result which is also illustrated in fig 7. 44.1% public has shown positive sentiments, 26.5% has shown negative and 29.5% has shown neutral reaction.