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Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
[article]
2021
arXiv
pre-print
The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as PolitiFact, robust detection techniques are required to deal with the increase in fake news. Several deep learning models show promising results for fake news classification, however, their black-box nature makes it difficult to explain their classification decisions and quality-assure the models. We here address this
arXiv:2105.09114v1
fatcat:edw4zmbmgvhgzdaucsgzzcogwm