Covid19 is one of the major problem in everybody's life and it has also paved a way for other problems such as Oxygen Scarsity, lack of beds in hospitals, unavailable right blood match and these problems have created a chaos in the society. Twitter is large platform where lot of volunteers posting details and links about the resources. But sometime these resource can go outdated or not genuine. And this can misguide people who are looking such information.
So to overcome this problem we have used natural language processing in order to analyse the tweets and classify based on priority. For the user convinence we have build App and website where it allows user to use the service and if they find if the info is not genuine then they can down vote or if they find its verified then can upvote it. Based on the votes the system classifyies the genuine and spam tweets and guide the users right way.
Actually the scrapped twitter data was not in a good order. Later using Datascience concepts we cleaned the complete data.
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