Big data as a modern criminological method of studying and measuring organized crime

Abstract

The paper is devoted to the study, measurement and assessment of organized crime in Russia, and to researching the possibility of using «big data» to analyze crime. As the task of counteracting crime is getting more and more complicated, it becomes necessary to reconsider both the traditional methods of researching crime, and the possibilities of going beyond the boundaries of such methods. The existing forms of state statistical reporting reflect only certain crimes committed by organized criminal groups and, in exceptional cases - by criminal communities. The use of official state statistics to measure the level of organized crime leads to numerous distortions in its evaluation. In some cases, all it can do is indicate the trend. There is no assessment of the actual condition of this criminological problem due to a high complexity of measurements, of choosing the technique of information collection and analysis, as well as the theoretical model of predicting organized crime, forecasting its future trends and regularities. In the last decade, the countries where digital technologies are developing actively have witnessed an intensified interest to the use of computing and intellectual methods of analyzing organized crime. The main achievement of science is that there is a widespread understanding among criminologists involved in research that the existing instruments, methods and programs for the intellectual analysis of structured and unstructured data are sufficient for the transition to computational criminology. «Big data» have a special place in the structure of information technologies. The development of data collection and analysis technologies makes it possible to measure criminality at a conceptually new level. A significant growth in the volume of data, the sources and dissemination tools of which are social objects, leads to the establishment of new technologies of processing the information on crimes. The presented article shows the necessity of using a large volume of structured and unstructured data to study and evaluate qualitative parameters of organized crime. This presents considerable opportunities for using «big data» to predict the trends of future changes in organized crime, as well as for applying new technologies to the theory and practice of preventing organized crime. The prediction and prevention of organized crime are considered to be rather difficult, and sometimes impossible when it concerns finding empirical proof and, moreover, obtaining prediction verification of some or other concept. Consequently, up to now traditional research approaches have not been effective in the sphere of researching organized crime. Meanwhile, law enforcement bodies need knowledge on the structure of crime, on the emergence of new forms of organizing criminal groups, on changes in criminal behavior connected with the technologies of the new technological revolution, etc.