@InProceedings{malmasi-zampieri:2017:RANLP,
  author    = {Malmasi, Shervin  and  Zampieri, Marcos},
  title     = {Detecting Hate Speech in Social Media},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {467--472},
  abstract  = {In this paper we examine methods to detect hate speech in social media, while
	distinguishing this from general profanity. We aim to establish lexical
	baselines for this task by applying supervised classification methods using a
	recently released dataset annotated for this purpose. As features, our system
	uses character n-grams, word n-grams and word skip-grams. We obtain results of
	78% accuracy in identifying posts across three classes. Results demonstrate
	that the main challenge lies in discriminating profanity and hate speech from
	each other. A number of directions for future work are discussed.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_062}
}