@InProceedings{plazadelarco-EtAl:2019:S19-23,
  author    = {Plaza del Arco, Flor Miriam  and  Molina González, M. Dolores  and  Martin, Maite  and  Urena Lopez, L. Alfonso},
  title     = {SINAI at SemEval-2019 Task 6: Incorporating lexicon knowledge into SVM learning to identify and categorize offensive language in social media},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {735--738},
  abstract  = {Offensive language has an impact across society. The use of social media has aggravated this issue among online users, causing suicides in the worst cases. For this reason, it is important to develop systems capable of identifying and detecting offensive language in text automatically. In this paper, we developed a system to classify offensive tweets as part of our participation in SemEval-2019 Task 6: OffensEval. Our main contribution is the integration of lexical features in the classification using the SVM algorithm.},
  url       = {http://www.aclweb.org/anthology/S19-2129}
}