Graphical Visualization of the Connections of Involved Users and Identifying Influential Spreaders in a Social Network

According to the latest research, the use of social media to track the spread of radical ideas and extremist threats has attracted the attention of researchers for over 10 years. In recent years, there has been a surge in research interest in identifying criminals through social media accounts and analyzing the visualization of the connections of the users involved, since criminals actively use social media, and the number of calls for extremism through social media is growing every year. In this paper, we consider the current problem of using identification methods based on public data of user profiles and social network analysis to identify nodes for the dissemination of criminal information in social networks. It provides an overview of existing solutions and approaches, as well as proposes a proprietary method for identifying user profiles and analyzing graph properties. The applicability of the proposed method has been demonstrated experimentally through testing real datasets. The results of the experiment show high accuracy in detecting engaged users.