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 kind of discourse there is 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.
@article{arxiv.1704.05972,
title = {SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours},
author = {Leon Derczynski and Kalina Bontcheva and Maria Liakata and Rob Procter and Geraldine Wong Sak Hoi and Arkaitz Zubiaga},
journal= {arXiv preprint arXiv:1704.05972},
year = {2017}
}