An improved method of detecting false information

Abstract

Under the conditions of the rapid development of the global information society, the widespread use of information and communication technologies in all spheres of life, the problem of information security acquires special importance. Technology, a double-edged sword in this battle, also has the potential to solve the problem. Fact-checking algorithms, while imperfect, can act as sentinels by flagging suspicious content. Transparency and collaboration between platforms, researchers and independent fact-checkers are critical to improving these tools and ensuring responsible use. However, technology alone cannot win this war. The battlefield goes beyond algorithms and code, reaching into the very fabric of our societies. Current methods of detecting false information take into account only the content of the data source, that is, the data itself, without paying attention to the context of the data. Taking into account that data is becoming more complex, it is becoming more and more, it becomes important to develop and improve algorithms and methods for detecting false information, taking into account the modern features of information dissemination. Therefore, the purpose of the work is to develop an improved method of detecting false information based on the synergy of the proposed additional methods. The improvement of the method consists in the synergy of the five components. Each of which has the ability to detect false information with some probability. It is the synergy and combinatorics of these methods that improve the overall method and detect false information with greater efficiency than existing methods.