Detection and Resolution of Rumors and Misinformation with NLP

Leon Derczynski, Arkaitz Zubiaga

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstrakt

Detecting and grounding false and misleading claims on the web has grown to form a substantial sub-field of NLP. The sub-field addresses problems at multiple different levels of misinformation detection: identifying check-worthy claims; tracking claims and rumors; rumor collection and annotation; grounding claims against knowledge bases; using stance to verify claims; and applying style analysis to detect deception. This half-day tutorial presents the theory behind each of these steps as well as the state-of-the-art solutions.
OriginalsprogEngelsk
TitelProceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts
UdgivelsesstedBarcelona, Spain (Online)
ForlagAssociation for Computational Linguistics
Publikationsdatodec. 2020
Sider22-26
ISBN (Elektronisk)978-1-952148-30-9
DOI
StatusUdgivet - dec. 2020

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