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INTERNET AGGRESSION ACTS DETECTION IN SOCIAL NETWORKS USING DATA MINING ALGORITHMS

Krepak Ivan   (graduate student, Department of Information Security, Financial University under the Government of the Russian Federation, Moscow )

IT development, in addition to an enormous benefit to humanity in solving everyday and entertainment problems, has brought many unsolved problems due to their incorrect use. Most of these challenges are beyond the law and are cybercrimes. One of the types of cybercrime, which is currently one of the most active, is Internet bullying. Acts of cyberbullying have undergone a large number of changes and now not only children, but also teenagers and adults become victims of Internet aggression. Social networks are both mass media and platforms where computer aggression often occurs and is almost uncontrolled (difficult to suppress). This article is devoted to the analysis of the frequency of background acts of Internet bullying in the network segment of the CIS. Collection and processing of the results took place in several stages, such as the formation of a knowledge base, preliminary processing, statistical analysis of the importance of keywords in the context of text files, data verification, and their classification. The results showed a high prevalence of the problem and a high frequency of background acts of computer aggression.

Keywords:Internet crime, cyberbullying, automation, social network, telecommunications, data mining, machine learning, API, database, web page
 

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Citation link:
Krepak I. INTERNET AGGRESSION ACTS DETECTION IN SOCIAL NETWORKS USING DATA MINING ALGORITHMS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№03. -С. 83-86 DOI 10.37882/2223-2966.2025.03.27
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