Twitter Fake News Detection Using Graph Neural Networks

Authors

  • Victor Sineglazov National Aviation University, Kyiv, Ukraine https://orcid.org/0000-0002-3297-9060
  • Kyrylo Bylym National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

DOI:

https://doi.org/10.18372/1990-5548.78.18259

Keywords:

fake news detection, graph neural networks, Twitter, binary classification, graph pooling

Abstract

This article is devoted to the intellectual processing of text information for the purpose of detecting rail news. To solve the given task, the use of deep graph neural networks is proposed. Fake news detection based on user preferences is augmented with deeper graph neural network topologies, including Hierarchical Graph Pooling with Structure Learning, to improve the graph convolution operation and capture richer contextual relationships in news graphs. The paper presents the possibilities of extending the framework of fake news detection based on user preferences using deep graph neural networks to improve fake news recognition. Evaluation on the FakeNewsNet dataset (a subset of Gossipcop) using the PyTorch Geometric and PyTorch Lightning frameworks demonstrates that the developed deep graph neural network model achieves 94% accuracy in fake news classification. The results show that deeper graph neural networks with integrated text and graph features offer promising options for reliable and accurate fake news detection, paving the way for improved information quality in social networks and beyond.

Author Biographies

Victor Sineglazov , National Aviation University, Kyiv, Ukraine

Doctor of Engineering Science

Professor.

Head of the Department Aviation Computer-Integrated Complexes

Faculty of Air Navigation Electronics and Telecommunications

Kyrylo Bylym , National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Graduate Student

Department of Artificial Intelligence

Institute of Applied System Analysis

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Published

2023-12-27

How to Cite

Sineglazov , V., & Bylym , K. (2023). Twitter Fake News Detection Using Graph Neural Networks. Electronics and Control Systems, 4(78), 26–33. https://doi.org/10.18372/1990-5548.78.18259

Issue

Vol. 4 No. 78 (2023)

Section

COMPUTER SCIENCES AND INFORMATION TECHNOLOGIES

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