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This paper presents our approach to the Task 5 of Semeval-2019, which aims at detecting hate speech against immigrants and women in Twitter. The task consists of two subtasks, in Spanish and English: (A) detection of hate speech and (B) classification of hateful tweets as aggressive or not, and identification of the target harassed as individual or group. We used linguistically motivated features and several types of n-grams (words, characters, functional words, punctuation symbols, POS, amongdoi:10.18653/v1/s19-2079 dblp:conf/semeval/VegaRGB19 fatcat:rzdl4gwtenfhreowa56dgjsa2m