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.
Type
Publication
Proceedings of the workshop on Semantic Evaluation (SemEval)
Leon Derczynski
Associate professor
My research interests include NLP for misinformation detection and verification, clinical record processing, online harms, and efficient AI.