CrotoneMilano for AMI at Evalita2018. A performant, cross-lingual misogyny detection system.
Angelo Basile, Chiara Rubagotti · Accademia University Press eBooks · 2018
We present our systems for misogyny identification on Twitter, for Italian and English. The models are based on a Support Vector Machine and they use n-grams as features. Our solution is very simple and yet we achieve top results on Italian Tweets and excellent results on English Tweets. Furthermore, we experiment with a single model that works across languages by leveraging abstract features. We show that a single multi-lingual system yields performances comparable to two independently trained systems. We achieve accuracy results ranging from 45% to 85%. Our system is ranked first out of twelve submissions for sub-task B on Italian and second for sub-task A.