@InProceedings{nogueiradossantos-melnyk-padhi:2018:Short,
  author    = {Nogueira dos Santos, Cicero  and  Melnyk, Igor  and  Padhi, Inkit},
  title     = {Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {189--194},
  abstract  = {We introduce a new approach to tackle the problem of offensive language in online social media. Our approach uses unsupervised text style transfer to translate offensive sentences into non-offensive ones. We propose a new method for training encoder-decoders using non-parallel data that combines a collaborative classifier, attention and the cycle consistency loss. Experimental results on data from Twitter and Reddit show that our method outperforms a state-of-the-art text style transfer system in two out of three quantitative metrics and produces reliable non-offensive transferred sentences.},
  url       = {http://www.aclweb.org/anthology/P18-2031}
}