TY - GEN
T1 - Improving Hate Speech Type and Target Detection with Hateful Metaphor Features
AU - Lemmens, Jens
AU - Markov, Ilia
AU - Daelemans, Walter
PY - 2021
Y1 - 2021
N2 - We study the usefulness of hateful metaphors as features for the identification of the type and target of hate speech in Dutch Facebook comments. For this purpose, all hateful metaphors in the Dutch LiLaH corpus were annotated and interpreted in line with Conceptual Metaphor Theory and Critical Metaphor Analysis. We provide SVM and BERT/RoBERTa results, and investigate the effect of different metaphor information encoding methods on hate speech type and target detection accuracy. The results of the conducted experiments show that hateful metaphor features improve model performance for the both tasks. To our knowledge, it is the first time that the effectiveness of hateful metaphors as an information source for hate speech classification is investigated.
AB - We study the usefulness of hateful metaphors as features for the identification of the type and target of hate speech in Dutch Facebook comments. For this purpose, all hateful metaphors in the Dutch LiLaH corpus were annotated and interpreted in line with Conceptual Metaphor Theory and Critical Metaphor Analysis. We provide SVM and BERT/RoBERTa results, and investigate the effect of different metaphor information encoding methods on hate speech type and target detection accuracy. The results of the conducted experiments show that hateful metaphor features improve model performance for the both tasks. To our knowledge, it is the first time that the effectiveness of hateful metaphors as an information source for hate speech classification is investigated.
UR - https://hdl.handle.net/10067/1803230151162165141
U2 - 10.18653/V1/2021.NLP4IF-1.2
DO - 10.18653/V1/2021.NLP4IF-1.2
M3 - Conference contribution
BT - Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda
ER -