The article addresses the problem of detecting unreliable news content and proposes a solution based on machine learning methods. Modern approaches to assessing the credibility of textual and multimedia content have been analyzed, promising techniques have been identified and adapted for the Russian-language media environment. A combined method for detecting fake news is proposed, based on the joint analysis of textual and multimedia data, as well as content distribution patterns. Testing of the proposed method has confirmed its effectiveness and applicability for automated detection of unreliable news content in real-world information systems.