@inproceedings{uludogan-etal-2024-detecting,
title = "Detecting Hate Speech in {T}urkish Print Media: A Corpus and A Hybrid Approach with Target-oriented Linguistic Knowledge",
author = {Uludo{\u{g}}an, G{\"o}k{\c{c}}e and
Y{\"u}ksel, At{\i}f Emre and
Tun{\c{c}}er, {\"U}mit and
I{\c{s}}{\i}k, Burak and
Korkmaz, Yasemin and
Akar, Didar and
{\"O}zg{\"u}r, Arzucan},
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Tanev, Hristo and
Thapa, Surendrabikram and
Uludo{\u{g}}an, G{\"o}k{\c{c}}e},
booktitle = "Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.case-1.29",
pages = "205--214",
abstract = "The use of hate speech targeting ethnicity, nationalities, religious identities, and specific groups has been on the rise in the news media. However, most existing automatic hate speech detection models focus on identifying hate speech, often neglecting the target group-specific language that is common in news articles. To address this problem, we first compile a hate speech dataset, TurkishHatePrintCorpus, derived from Turkish news articles and annotate it specifically for the language related to the targeted group. We then introduce the HateTargetBERT model, which integrates the target-centric linguistic features extracted in this study into the BERT model, and demonstrate its effectiveness in detecting hate speech while allowing the model{'}s classification decision to be explained. We have made the dataset and source code publicly available at url{https://github.com/boun-tabi/HateTargetBERT-TR}.",
}
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<abstract>The use of hate speech targeting ethnicity, nationalities, religious identities, and specific groups has been on the rise in the news media. However, most existing automatic hate speech detection models focus on identifying hate speech, often neglecting the target group-specific language that is common in news articles. To address this problem, we first compile a hate speech dataset, TurkishHatePrintCorpus, derived from Turkish news articles and annotate it specifically for the language related to the targeted group. We then introduce the HateTargetBERT model, which integrates the target-centric linguistic features extracted in this study into the BERT model, and demonstrate its effectiveness in detecting hate speech while allowing the model’s classification decision to be explained. We have made the dataset and source code publicly available at urlhttps://github.com/boun-tabi/HateTargetBERT-TR.</abstract>
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%0 Conference Proceedings
%T Detecting Hate Speech in Turkish Print Media: A Corpus and A Hybrid Approach with Target-oriented Linguistic Knowledge
%A Uludoğan, Gökçe
%A Yüksel, Atıf Emre
%A Tunçer, Ümit
%A Işık, Burak
%A Korkmaz, Yasemin
%A Akar, Didar
%A Özgür, Arzucan
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Thapa, Surendrabikram
%Y Uludoğan, Gökçe
%S Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F uludogan-etal-2024-detecting
%X The use of hate speech targeting ethnicity, nationalities, religious identities, and specific groups has been on the rise in the news media. However, most existing automatic hate speech detection models focus on identifying hate speech, often neglecting the target group-specific language that is common in news articles. To address this problem, we first compile a hate speech dataset, TurkishHatePrintCorpus, derived from Turkish news articles and annotate it specifically for the language related to the targeted group. We then introduce the HateTargetBERT model, which integrates the target-centric linguistic features extracted in this study into the BERT model, and demonstrate its effectiveness in detecting hate speech while allowing the model’s classification decision to be explained. We have made the dataset and source code publicly available at urlhttps://github.com/boun-tabi/HateTargetBERT-TR.
%U https://aclanthology.org/2024.case-1.29
%P 205-214
Markdown (Informal)
[Detecting Hate Speech in Turkish Print Media: A Corpus and A Hybrid Approach with Target-oriented Linguistic Knowledge](https://aclanthology.org/2024.case-1.29) (Uludoğan et al., CASE-WS 2024)
ACL