DETECTION OF MANIPULATIVE COMPONENT IN TEXT MESSAGES OF MASS MEDIA IN THE CONTEXT OF PROTECTION OF DOMESTIC CYBERSPACE

The problem of the article is to increase the effectiveness of information security means within the national cyberspace by automated detection of the manipulative component in text messages of the mass media. It is shown that one of the main directions of increasing the effectiveness of such means is the use of large language models, which are capable of performing a deep contextual analysis of a natural language text, taking into account emotional, rhetorical and semantic content. It is established that most of the known solutions in the field of detecting text manipulations using large language models are quite difficult to adapt to the conditions of practical application in systems for protecting domestic cyberspace due to the need to create a powerful hardware and software infrastructure to service the corresponding LLM-means and the need to form specialized training samples that take into account the main types of manipulative influences characteristic of the realities of information confrontation. To overcome these limitations, the article proposes a concept for using LLM tools (GPT, Gemini, DeepSeek, Grok, etc.), which is based on the implementation of dialogic interaction