To date, most research on hate speech within the NLP community has been done in the area of automatic detection using a variety of techniques, from lists of prominent keywords (Warner and Hirschberg, 2012) to regression classifiers as seen in the previous section (Nobata et al., 2016;<cite> Waseem and Hovy, 2016)</cite> , naive Bayes, decision trees, random forests, and linear SVMs , as well as deep learning models with convolutional neural networks (Gambäck and Utpal, 2017; Park and Fung, 2017) .