Mass Violence Detection Using Data Mining Techniques

The world is now witnessing a tectonic shift in the way in which people react to social and economic impacts such as rise in fossil fuel prices, implication of new rules and regulations, and other situations which directly affect the emotions of a certain group of people. Violence is the most widely used way of expressing anger and discontent for a particular situation which might have occurred. Such actions can cause loss of millions of dollars and precious lives of people who come in way of such protests. These protests are mainly conducted through social media platforms such as twitter as it is not possible to personally communicate to tens of thousand people to accumulate at a certain place, therefore it is extremely important as well as necessary to keep an eye on the social media statuses and updates of people in the times of crisis and heavy tension. This paper aims to collect the tweets of people uploaded on twitter and then process them to find out the location, time and intensity of the mass violence so that the responsible authorities can handle the situation and prevent violence.