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Data · dataset · 2026

Heterogeneity-Aware Continuous Graph Neural Diffusion Network for Unsupervised Fake News Detection (old)

Listed in Teesside University Research Data Repository

This record provides the source code and data-access metadata for HCGDN, the method presented in “Heterogeneity-Aware Continuous Graph Neural Diffusion Network for Unsupervised Fake News Detection.” HCGDN is an unsupervised graph representation learning framework for fake news detection.

Description

It models heterogeneous propagation structures through two complementary components: a global graph neural diffusion process for capturing long-range propagation dependencies and a local semantics-driven diffusion process for representing intensive substructures.

The release contains the model implementation, graph-construction and dataset-loading code, experiment configurations, evaluation procedures, and a locked dependency specification. The evaluation code uses stratified ten-fold MLP classification to assess the learned graph representations. The experiments reported in the associated manuscript use PolitiFact and GossipCop from FakeNewsNet, together with the Weibo benchmark described by Ma et al. The original news, user, comment, and social-media records are not redistributed in this record.

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Derived graph arrays and precomputed BERT feature matrices are also not included because they originate from third-party benchmark data and remain subject to the applicable upstream terms. PolitiFact and GossipCop should be obtained through the FakeNewsNet project: github.com/KaiDMML/FakeNewsNet The Weibo benchmark should be obtained from its original providers using the access and author-contact information associated with: doi.org/10.1145/3391250 After obtaining authorized access, users must prepare the local input files described in DATA_AVAILABILITY.md.

README.md provides the software environment, directory structure, configuration details, and execution command. This is HCGDN software release version 1.0.0. The source code and documentation are distributed under the MIT License.

The MIT License does not apply to FakeNewsNet, Weibo, or any original or derived dataset files.

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Catalogue records · 1

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From keywords
Artificial intelligence · Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
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