Methods and Software Tools for Recognizing Fake or Irrelevant Information in the Content of News-Oriented Social Networks.

Abstract

The dissertation is devoted to addressing a pressing scientific and technical problem—enhancing the effectiveness of detecting and analyzing fake content in newsoriented social networks under conditions of limited data samples. Modern information society is characterized by the rapid development of social networks, which have become one of the main channels for news dissemination, communication, and public opinion formation. Alongside the expansion of digital communication capabilities, the scale of the problem of spreading false or irrelevant information is also increasing, directly affecting information security, political stability, and public trust in the media.