Detecting the Spread of False News Content Using Machine Learning

Abstract

The problem of detecting unreliable news content is studied and a solution based on machine learning methods is proposed. Modern approaches used to assess the reliability of textual and multimedia content are analyzed, with promising approaches identified and adapted to the Russian-language media space. A combined method for detecting fake news is proposed, based on the joint analysis of textual and multimedia information, as well as the characteristics of content dissemination. Testing the proposed method confirmed its effectiveness and applicability for the automated detection of unreliable news content in real-world information systems.