SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours

Leon Derczynski, Kalina Bontcheva, Maria Liakata, Rob Procter, Geraldine Wong Sak Hoi, Arkaitz Zubiaga

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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.
Anthology ID:
S17-2006
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
69–76
Language:
URL:
https://aclanthology.org/S17-2006
DOI:
10.18653/v1/S17-2006
Bibkey:
Cite (ACL):
Leon Derczynski, Kalina Bontcheva, Maria Liakata, Rob Procter, Geraldine Wong Sak Hoi, and Arkaitz Zubiaga. 2017. SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 69–76, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours (Derczynski et al., SemEval 2017)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/S17-2006.pdf