Synergy of Digital Technologies and Graphic Modeling in Forensic Counteraction to the Spread of Extremism and Terrorism Ideology 215 Among the Youth

The article explores threats of an extremist and terrorist nature that spread in the Russian-language segment of the Internet. Content analysis of personal accounts on social networks plays a significant role in preventing and countering manifestations of extremism and terrorism in cyberspace. Such an analysis is fraught with a number of objective difficulties, which are based on a significant amount of information to be processed. The authors argue that the time spent on studying and analyzing social media accounts can be significantly reduced through mathematical algorithms. An analysis of the special legal literature on this issue showed that today, both in Russia and abroad, there are practically no studies that reveal the methodology of studying accounts on social networks in order to identify deviations of an extremist or terrorist nature. The aim of this study is to optimize the activities of law enforcement agencies to conduct content analysis of accounts on social networks. The object of the study was illegal activities of an extremist and terrorist nature carried out through the use of tools and capabilities of the social network VKontakte, as well as activities to identify, suppress, and prevent manifestations of extremism and terrorism in VKontakte. The methodological basis was the logical research methods: analysis, synthesis, modeling method; the proposed development is based on the provisions of graph theory. To solve the mentioned problems, the Immanuel Kant Baltic Federal University scientists developed a software package implemented in the programming language Python 3.1 using the Anaconda library package, which provides the ability to automatically extract various data from social networks. The authors describe in detail the principle of the configuration of the software complex and the algorithm of its functioning that allows segmenting the contacts of a social network user and their subsequent schematic visualizing in the form of a graph, which significantly reduces the time spent on content analysis. The software package also allows finding friendly relationships and, subsequently, build a graph among users who have liked a certain post on the Vkontakte network. The authors conclude that the use of the developed software package allows optimizing the activities of law enforcement officers in the content analysis of social network accounts of already identified extremists, preventing extremism on the Internet by identifying potentially dangerous communities and public pages through the analysis of the relationships of their subscribers, searching for persons holding extremely radical extremist views and who have not previously been the objects of close attention of law enforcement agencies.

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