Gorrell, G. orcid.org/0000-0002-8324-606X, Kochkina, E., Liakata, M. et al. (4 more authors) (2019) RumourEval 2019: Determining rumour veracity and support for rumours. In: May, J., Shutova, E., Herbelot, A., Zhu, X., Apidianaki, M. and Mohammad, S.M., (eds.) Proceedings of the 13th International Workshop on Semantic Evaluation. 13th International Workshop on Semantic Evaluation . Association for Computational Linguistics, pp. 845-854.
Abstract
Since the first RumourEval shared task in 2017, interest in automated claim validation has greatly increased, as the danger of “fake news” has become a mainstream concern. However automated support for rumour verification remains in its infancy. It is therefore important that a shared task in this area continues to provide a focus for effort, which is likely to increase. Rumour verification is characterised by the need to consider evolving conversations and news updates to reach a verdict on a rumour's veracity. As in RumourEval 2017 we provided a dataset of dubious posts and ensuing conversations in social media, annotated both for stance and veracity. The social media rumours stem from a variety of breaking news stories and the dataset is expanded to include Reddit as well as new Twitter posts. There were two concrete tasks; rumour stance prediction and rumour verification, which we present in detail along with results achieved by participants. We received 22 system submissions (a 70% increase from RumourEval 2017) many of which used state-of-the-art methodology to tackle the challenges involved.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2019 Association for Computational Linguistics. This paper is licensed under a Creative Commons Attribution 4.0 International License. https://creativecommons.org/licenses/by/4.0/ |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
| Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 654024 EUROPEAN COMMISSION - HORIZON 2020 COMRADES - 687847 |
| Date Deposited: | 03 Jul 2026 08:51 |
| Last Modified: | 03 Jul 2026 08:51 |
| Status: | Published |
| Publisher: | Association for Computational Linguistics |
| Refereed: | Yes |
| Identification Number: | 10.18653/v1/s19-2147 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:242860 |
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Filename: S19-2147.pdf
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