Modeling of terrorist activity in RSO-A

Abstract

The subject of the study is the modeling and forecasting of terrorist and extremist activity of RSO-A. This task is urgent, since terrorist activity around the world has remained very high in recent years and even a rough forecast allows us to take preventive measures in case of a possible aggravation of the situation. Usually, an analysis of the mechanisms of radicalization and the formation of extremist groups is used for forecasting. At the same time, the methods of game theory and machine learning and models of the spread of epidemic diseases are used. In all cases, the verification of models requires a large amount of initial information, which, as a rule, is missing. In addition, these models are applicable only for regions with a sufficiently high level of extremist and terrorist activity.The paper proposes a method for predicting terrorist and extremist activity for regions where its level is low. The method is based on the assumption that people who are not satisfied with their social status and do not see prospects for its improvement are involved in various radical groups and/or are inclined to extremism and terrorism. Since it is much easier to get into a radical group whose activities are not prohibited by law, the increase in the intensity of involvement in them outstrips the growth of extremist and terrorist activity and is its harbinger. The method is tested on the example of the Republic of North Ossetia-Alania, in which adherents of radical Islam are a typical radical group. It is shown that for RSO-A, terrorist activity in the region can be predicted by the intensity of involvement in radical groups with a lag of two years. The proposed model allows us to satisfactorily assess the change in terrorist activity in the Republic of North Ossetia-Alania for the period 2015-2019.