@InProceedings{gariboiorts:2019:S19-2,
  author    = {Garibo i Orts, Òscar},
  title     = {Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter at SemEval-2019 Task 5: Frequency Analysis Interpolation for Hate in Speech Detection},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {460--463},
  abstract  = {This document describes a text change of representation approach to the task of Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter, as part of SemEval-2019 1 . The task is divided in two sub-tasks. Sub-task A consists in classifying tweets as being hateful or not hateful, whereas sub-task B requires fine tuning the classification by classifying the hateful tweets as being directed to single individuals or generic, if the tweet is aggressive or not. Our approach consists of a change of the space of representation of text into statistical descriptors which characterize the text. In addition, dimensional reduction is performed to 6 characteristics per class in order to make the method suitable for a Big Data environment. Frequency Analysis Interpolation (FAI) is the approach we use to achieve rank 5th in Spanish language and 9th in English language in sub-task B in both cases.},
  url       = {http://www.aclweb.org/anthology/S19-2081}
}