Characterizing and Countering Communal Micro blogs During Disaster Events

Synopsis:

           Social media reach is widespread such that information travels very fast without any geographical border or constrained. People are forwarding information without checking the credibility of the message. In this scenario a tweet with hatred message also propagated swiftly leading to unrest in the society. To check these kinds of messages propagating and to find a way not to promote these messages, Machine learning technology is used to address these issues.

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.