Identifying Hate Speech Using Neural Networks and Discourse Analysis Techniques

Zehra Melce Hüsünbeyi, Didar Akar, Arzucan Özgür

Abstract
Discriminatory language, in particular hate speech, is a global problem posing a grave threat to democracy and human rights. Yet, it is not always easy to identify, as it is rarely explicit. In order to detect hate speech, we developed Hierarchical Attention Network (HAN) based and Bidirectional Encoder Representations from Transformer (BERT) based deep learning models to capture the changing discursive cues and understand the context around the discourse. In addition, we designed linguistic features using critical discourse analysis techniques and integrated them into these neural network models. We studied the compatibility of our model with the hate speech detection problem by comparing it with traditional machine learning models, as well as a Convolution Neural Network (CNN) based model, a Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU) based model which reached significant performance results for hate speech detection. Our results on a manually annotated corpus of print media in Turkish show that the proposed approach is effective for hate speech detection. We believe that the feature sets created for the Turkish language will encourage new studies in the quantitative analysis of hate speech.
Anthology ID:
2022.lateraisse-1.5
Volume:
Proceedings of the First Workshop on Language Technology and Resources for a Fair, Inclusive, and Safe Society within the 13th Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Kolawole Adebayo, Rohan Nanda, Kanishk Verma, Brian Davis
Venue:
LATERAISSE
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
32–41
Language:
URL:
https://aclanthology.org/2022.lateraisse-1.5
DOI:
Bibkey:
Cite (ACL):
Zehra Melce Hüsünbeyi, Didar Akar, and Arzucan Özgür. 2022. Identifying Hate Speech Using Neural Networks and Discourse Analysis Techniques. In Proceedings of the First Workshop on Language Technology and Resources for a Fair, Inclusive, and Safe Society within the 13th Language Resources and Evaluation Conference, pages 32–41, Marseille, France. European Language Resources Association.
Cite (Informal):
Identifying Hate Speech Using Neural Networks and Discourse Analysis Techniques (Hüsünbeyi et al., LATERAISSE 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/improve-issue-templates/2022.lateraisse-1.5.pdf
PDF Search