In recent years, world has been hit by so many natural disasters which has adverse events of the Earth; they consist of floods, volcanic eruptions, earthquakes, tsunamis, hurricanes, tornado, landslides and other geologic processes. Some of the examples of recent natural disasters are devastating floods and landslides in Uttarakhand on June 2013, a volcanic eruption in Japan in 2014, tsunami in Japan on March 2011. These disasters remind us that we are far away from the prepared emergencies. In this paper I have examined the real-time interaction of incidents of Natural Disasters, in Twitter, and designed an algorithm to examine tweets and to discover goal events. To detect goal events, I have work out on collecting Twitter data, looking at free APIs provided by Twitter and also categorization of tweets on basis of aspects such as the keywords in a tweet. I have also worked out in storing Twitter data in a tangible way for use in real-time application and constituted a secular model to calculate time of happening of the event. Finally, I have used Python to show the analysis as a result where common measures and algorithms are used to analyse the data