@inproceedings{najafi-varol-2024-vrllab,
title = "{VRLL}ab at {HSD}-2{L}ang 2024: {T}urkish Hate Speech Detection Online with {T}urkish{BERT}weet",
author = "Najafi, Ali and
Varol, Onur",
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-1.25",
pages = "185--189",
abstract = "Social media platforms like Twitter - recently rebranded as X - produce nearly half a billion tweets daily and host a significant number of users that can be affected by content that are not properly moderated. In this work, we present an approach that ranked third at the HSD-2Lang 2024 competition{'}s subtask-A along with additional methodology developed for this task and evaluation of different approaches. We utilize three different models and the best performing approach use publicly-available TurkishBERTweet model with low-rank adaptation (LoRA) for fine tuning. We also experiment with another publicly available model and a novel methodology to ensemble different hand-crafted features and outcomes of different models. Finally, we report the experimental results, competition scores, and discussion to improve this effort further.",
}
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%0 Conference Proceedings
%T VRLLab at HSD-2Lang 2024: Turkish Hate Speech Detection Online with TurkishBERTweet
%A Najafi, Ali
%A Varol, Onur
%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 najafi-varol-2024-vrllab
%X Social media platforms like Twitter - recently rebranded as X - produce nearly half a billion tweets daily and host a significant number of users that can be affected by content that are not properly moderated. In this work, we present an approach that ranked third at the HSD-2Lang 2024 competition’s subtask-A along with additional methodology developed for this task and evaluation of different approaches. We utilize three different models and the best performing approach use publicly-available TurkishBERTweet model with low-rank adaptation (LoRA) for fine tuning. We also experiment with another publicly available model and a novel methodology to ensemble different hand-crafted features and outcomes of different models. Finally, we report the experimental results, competition scores, and discussion to improve this effort further.
%U https://aclanthology.org/2024.case-1.25
%P 185-189
Markdown (Informal)
[VRLLab at HSD-2Lang 2024: Turkish Hate Speech Detection Online with TurkishBERTweet](https://aclanthology.org/2024.case-1.25) (Najafi & Varol, CASE-WS 2024)
ACL