%0 Conference Proceedings %T Detection and Resolution of Rumors and Misinformation with NLP %A Derczynski, Leon %A Zubiaga, Arkaitz %Y Specia, Lucia %Y Beck, Daniel %S Proceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts %D 2020 %8 December %I International Committee for Computational Linguistics %C Barcelona, Spain (Online) %F derczynski-zubiaga-2020-detection %X 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. %R 10.18653/v1/2020.coling-tutorials.4 %U https://aclanthology.org/2020.coling-tutorials.4 %U https://doi.org/10.18653/v1/2020.coling-tutorials.4 %P 22-26