ON THE ISSUE OF IDENTIFYING DESTRUCTIVE BEHAVIOR BASED ON TEXT DATA ANALYSIS USING MACHINE LEARNING METHODS

Teterin N. N., Smolentseva V. V.

The problem of identifying destructive behavior of Internet users based on the analysis of text data considered in the paper is an effective tool for preventing the consequences of destructive behavior. Destructive behavior, including cyberbullying, trolling, and hate speech, is a serious problem for online communities. The paper proposes an approach based on machine learning and natural language processing (NLP) methods based on the example of identifying destructive behavior. Experiments have been conducted using various classification algorithms, such as Random Forest, as well as text preprocessing methods. The results show that the proposed approach makes it possible to effectively identify destructive behavior.

Keywords:Destructive behavior, machine learning, forecasting, natural language processing, Internet users.