Fake posts detection using graph neural networks

The paper is devoted to the study of graph neural networks as a separate field and the possibility of their application to solve such an urgent cybersecurity problem as the detection of fake posts. The implementation of a proprietary graph neural network model capable of detecting fake posts is presented, and the results of experimental studies demonstrating the effectiveness of using graph neural networks to solve the problem are presented