@InProceedings{han-toner:2017:SemEval,
  author    = {Han, Xiwu  and  Toner, Gregory},
  title     = {QUB at SemEval-2017 Task 6: Cascaded Imbalanced Classification for Humor Analysis in Twitter},
  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     = {380--384},
  abstract  = {This paper presents our submission to SemEval-2017 Task 6: \#HashtagWars:
	Learning a Sense of Humor. There are two subtasks: A. Pairwise Comparison, and
	B. Semi-Ranking. Our assumption is that the distribution of humorous and
	non-humorous texts in real life language is naturally imbalanced. Using Na\"{i}ve
	Bayes Multinomial with standard text-representation features, we approached
	Subtask B as a sequence of imbalanced classification problems, and optimized
	our system per the macro-average recall. Subtask A was then solved via the
	Semi-Ranking results. On the final test, our system was ranked 10th for Subtask
	A, and 3rd for Subtask B.},
  url       = {http://www.aclweb.org/anthology/S17-2063}
}