Catastrophe alert system using social networks

The unbelievable growth and amount of information spread of social media helps the discovering of the new age result oriented recommender systems. Unfortunately the orthodoxies in the current system and the previous generation systems are structure oriented. For example rely mostly on the relativity of the network and the social demography. The investigative points discussed in this paper are generally based on the relative side of the communal factors. So the exploration leads naturally to the collaboration of the real time single directional social media dataset like twitter and the natural calamity events like cyclone, typhoons, earthquakes, Tsunami etc. The need for an interactive message application is higher than any other time because most of the countries are located at the geographically vulnerable point for earthquake invoked tsunami. So to probe such unfortunate event, there we require a vector backed machine of tweets which is based on the keyword, total no of words, etc. The location is estimated based on spatio-temporal pattern of events filtering. It will identify every user as a sensor and calculates. Whenever an earthquake occurs the report will be generated and forwarded to the user and the team of rescuers at the same time. So we can consider this as the fastest way when compared to the traditional JMA broadcast.