Characterizing and Countering Communal Microblogs During Disaster Events

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Aim:

The objective of this project is to develop a system to identify the tweet harbor hatred in micro blogs during disaster events.

Existing System:

The existing system uses sentiment analysis technique to identify the sentiment of the tweet. However this is not sufficient to identify the anti-social messages. The sentiment analysis might give the indication of the emotion related to positive or negative. But it is important to classify whether the tweets considered hatred.

Proposed system:

We propose a machine learning based classification algorithm to analyze the live tweet. In this system we are using a classifier to identify the words used in the tweet. The algorithm takes specific keywords list as input and the tweet to be identified as another input. The results were plotted in a graph.