Abstract

This scientific article analyzes and characterizes various types of false information disseminated in modern information systems. The main focus is on detecting and identifying the dangers associated with the spread of unreliable information in society. The serious consequences of this phenomenon can reach a global scale, making effective countermeasures critically important. The study examines and compares various software methods to counter the dissemination of false information. In particular, different methods of analyzing and filtering information aimed at detecting and localizing unreliable messages were studied and compared. This helps identify the most effective approaches to data analysis in the field of information systems and determine optimal methods to combat the spread of fake news. The conclusions of this research have practical applications and can be used to improve the analysis of information from various sources in information systems. The implementation of the solutions developed in this research will contribute to increasing the level of credibility and objectivity in information processing, thereby enhancing the quality of information analysis and its utilization in various sectors of society.

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