MODIFIED SEIRA MODELS OF THE SPREAD OF DISINFORMATION ON THE INTERNET

Authors

  • Vіoleta Tretynyk National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
  • Mykola Davydenko National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»

Keywords:

spread of disinformation, information security , graph neural networks (GNN), SEIRA model

Abstract

In the context of a full-scale war, a country's information security becomes critically important. The information space is highly saturated with various sources, and fake news often serves as a tool for destabilizing public sentiment. The spread of disinformation can be interpreted similarly to the spread of a virus, where users transition between different states. This paper explores approaches to detecting disinformation and modeling the dynamics of its diffusion.

References

Zhang J, et al. Graph neural networks: A review of methods and applications. Journal of Big Data. 2023. https://doi.org/10.1186/s40537-023-00876-4

Kipf TN, Welling M. Semi-supervised classification with graph convolutional networks. 2016. arXiv preprint arXiv:1609.02907.

Published

2025-06-03