During bulk convergence events such as natural disasters, microblogging platforms like Twitter are broadly used by affected people to post situational awareness messages. As soon as natural disaster events happen, users are willing to know more about them. Twitter is a great source that can be exploited for obtaining such fine-grained arranged information for fresh natural disaster events. These crisisrelated messages disperse among multiple categories like infrastructure damage, information about bomb blast, missing, injured, and dead people etc. The challenge here is to create summary from disaster related tweets and filter the short spam url containing tweets.
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