19/08/2021

Weaving a Semantic Web of Credibility Reviews for Explainable Misinformation Detection (Extended Abstract)

Ronald Denaux, Martino Mensio, Jose Manuel Gomez-Perez, Harith Alani

Keywords: Knowledge Representation and Reasoning, Semantic Web, Societal Impact of AI, Explainability, NLP Applications and Tools

Abstract: This paper summarises work where we combined semantic web technologies with deep learning systems to obtain state-of-the art explainable misinformation detection. We proposed a conceptual and computational model to describe a wide range of misinformation detection systems based around the concepts of credibility and reviews. We described how Credibility Reviews (CRs) can be used to build networks of distributed bots that collaborate for misinformation detection which we evaluated by building a prototype based on publicly available datasets and deep learning models.

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