Methods for determining fake news in social networks using machine learning
Fake-news existed long before the advent ofthe Internet and spread very quickly by all possible means of communication, being thus an effective tool of influence on public opinion. Many large IT companies, such as Google and Facebook, are developing their own algorithms to protect users from information falsification. At the same time, the lack of a unified approach to understanding the essence of counterfeit news makes the solution of this problem at least difficult. This problem requires serious study by relevant experts and scientists from different fields. In the framework of this study, an analysis is made of the mechanisms for publishing and disseminating fake news, their classification, structure and construction features are given. The research team demonstrates one of the possible solutions to the problem through methods of determining this type of news in social media, based on the use of systems with elements of artificial intelligence and machine learning.