@InProceedings{park-fung:2017:ALW1,
  author    = {Park, Ji Ho  and  Fung, Pascale},
  title     = {One-step and Two-step Classification for Abusive Language Detection on Twitter},
  booktitle = {Proceedings of the First Workshop on Abusive Language Online},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, BC, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {41--45},
  abstract  = {Automatic abusive language detection is a difficult but important task for
	online social media. Our research explores a two-step approach of performing
	classification on abusive language and then classifying into specific types and
	compares it with one-step approach of doing one multi-class classification for
	detecting sexist and racist languages. With a public English Twitter corpus of
	20 thousand tweets in the type of sexism and racism, our approach shows a
	promising performance of 0.827 F-measure by using HybridCNN in one-step and
	0.824 F-measure by using logistic regression in two-steps.
	Author{2}{Affiliation}},
  url       = {http://www.aclweb.org/anthology/W17-3006}
}