A model of the space of thematic telegram channels based on contextual links

The paper analyzes the existing models for describing the topology of the news web space, which reflect its division into coherent components such as its central part and peripheral areas, and proposes a new network model of thematic Telegram channels based on the idea of assessing the level of citation of individual information channels and taking into account direct links in messages from Telegram channels. It combines the content aspect of messages with the ability to take into account quantitative parameters. The study focuses on channels dedicated to cybersecurity and covers the first quarter of 2024. Based on the analysis of about 3,500 Telegram channels, more than 1,000 hyperlinked channels were identified and key areas of the information space, such as the communication zone, the communication core, and incoming and outgoing source segments, were outlined. The formed network is defined as a scale-free, structural network with self-similar properties and a power law distribution of node degrees, which confirms the applicability of the Pareto law to describe this space. A mathematical model is proposed that allows estimating the polynomial relationship between the volume of the communication area and the total number of sources. On the example of the CyberAggregator content monitoring system for information sources, a methodology for automated expansion of the database of target sources in the system is proposed, which provides dynamic enrichment of the list of information resources through the analysis of new contextual references in messages and an algorithm for its implementation.