@InProceedings{potash-romanov-rumshisky:2017:SemEval,
  author    = {Potash, Peter  and  Romanov, Alexey  and  Rumshisky, Anna},
  title     = {SemEval-2017 Task 6: \#HashtagWars: Learning a Sense of Humor},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {49--57},
  abstract  = {This paper describes a new shared task for humor understanding that attempts to
	eschew the ubiquitous binary approach to humor detection and focus on
	comparative humor ranking instead. The task is based on a new dataset of funny
	tweets posted in response to shared hashtags, collected from the `Hashtag Wars'
	segment of the TV show $@$midnight. The results are evaluated in two subtasks
	that require the participants to generate either the correct pairwise
	comparisons of tweets (subtask A), or the correct ranking of the tweets
	(subtask B) in terms of how funny they are. 7 teams participated in subtask A,
	and 5 teams participated in subtask B. The best accuracy in subtask A was
	0.675. The best (lowest) rank edit distance for subtask B was 0.872.},
  url       = {http://www.aclweb.org/anthology/S17-2004}
}