Derczynski, L., Bontcheva, K. orcid.org/0000-0001-6152-9600, Liakata, M. et al. (3 more authors) (2017) SemEval-2017 Task 8: RumourEval: determining rumour veracity and support for rumours. In: Bethard, S., Carpuat, M., Apidianaki, M., Mohammad, S.M., Cer, D.M. and Jurgens, D., (eds.) Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017). SemEval-2017 International Workshop on Semantic Evaluation, 03-04 Aug 2017, Vancouver, Canada. Association for Computational Linguistics , pp. 69-76. ISBN 978-1-945626-55-5
Abstract
Media is full of false claims. Even Oxford Dictionaries named “post-truth” as the word of 2016. This makes it more important than ever to build systems that can identify the veracity of a story, and the nature of the discourse around it. RumourEval is a SemEval shared task that aims to identify and handle rumours and reactions to them, in text. We present an annotation scheme, a large dataset covering multiple topics - each having their own families of claims and replies - and use these to pose two concrete challenges as well as the results achieved by participants on these challenges.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Feb 2025 10:22 |
Last Modified: | 14 Feb 2025 10:22 |
Status: | Published |
Publisher: | Association for Computational Linguistics |
Refereed: | Yes |
Identification Number: | 10.18653/v1/S17-2006 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:223254 |