In this assignment I am finding out peoples sentiment about DeMonetisation happened in india. Demonetization means the old unit of currency must be retired and replaced with a new currency unit. This is currently trending issue in India and people have both positive and negative sentiments about. I am collecting tweets which has #DeMonetisation using search API of twitter and classifying them as Positive and negative sentiment based on train data which will train model.In cluster.py i am finding out users who has tweeted about this issue and using there id am also Collecting whom they follow, using this information i am creating graph which will be one big component. This graph i am dividing in different communities using girvan newman. This information i am using to find out average user per community and sentiments of that community. In classify.py I am finding out positive and negative sentiments of people from tweets collected. To find out positive and negative sentiments of people, first i am training my model using train data which Is classifies using AFINN. Then i am collecting live twitter data which will be my test data, and then i am classifying this data as positive and negative sentiments. In summarize.py file i am showing final analysis. By looking at data in file we can say that more people having negative sentiments about DeMonetisation issue and people unhappy about the government decision while there are some people which are happy about government decision and having positive sentiment.