PANACEA: an automated misinformation detection system on COVID-19

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dc.contributor.authorZhao, Runcong
dc.contributor.authorArana-Catania, Miguel
dc.contributor.authorZhu, Lixing
dc.contributor.authorKochkina, Elena
dc.contributor.authorGui, Lin
dc.contributor.authorZubiaga, Arkaitz
dc.contributor.authorProcter, Rob
dc.contributor.authorLiakata, Maria
dc.contributor.authorHe, Yulan
dc.date.accessioned2023-08-08T13:50:00Z
dc.date.available2023-08-08T13:50:00Z
dc.date.issued2023-05-04
dc.description.abstractIn this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language inference methods with a self-attention network, outperforms state-ofthe-art approaches. It is also able to give automated veracity assessment and ranked supporting evidence with the stance towards the claim to be checked. In addition, PANACEA adapts the bi-directional graph convolutional networks model, which is able to detect rumours based on comment networks of related tweets, instead of relying on the knowledge base. This rumour detection module assists by warning the users in the early stages when a knowledge base may not be available.en_UK
dc.identifier.citationZhao R, Arana-Catania M, Zhu L, et al., (2023) PANACEA: an automated misinformation detection system on COVID-19. In: EACL 2023: The 17th Conference of the European Chapter of the Association for Computational Linguistics, 1-6 May 2023, Dubrovnik, Croatiaen_UK
dc.identifier.urihttps://aclanthology.org/2023.eacl-demo.9.pdf
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20066
dc.language.isoenen_UK
dc.publisherAssociation for Computational Linguisticsen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titlePANACEA: an automated misinformation detection system on COVID-19en_UK
dc.typeConference paperen_UK

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