Projects per year
Abstract
This study focuses on hate speech detection in Turkish and Arabic tweets using advanced BERT-based models. Performance metrics demonstrate the models' effectiveness, with the Turkish variant achieving a 71.8% F1 score and the Arabic model a 76.9% F1 score, ranking them fourth and third, respectively, in a competitive leaderboard. Performance enhancements were realized through targeted preprocessing, including emoji translation and user mention exclusion, and thoughtful data balancing approaches. Future directions include refining model accuracy and broadening language support. Our reproducible approach and detailed findings are accessible on GitHub.
Original language | English |
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Title of host publication | CASE 2024 - 7th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, Proceedings of the Workshop |
Editors | Ali Hurriyetoglu, Hristo Tanev, Surendrabikram Thapa, Gokce Uludogan |
Place of Publication | St Julians |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 215-220 |
Number of pages | 6 |
ISBN (Electronic) | 9798891760707 |
Publication status | Published - 2024 |
Event | 7th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, CASE 2024 - St. Julian's, Malta Duration: 22 Mar 2024 → … |
Conference/symposium
Conference/symposium | 7th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, CASE 2024 |
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Country/Territory | Malta |
City | St. Julian's |
Period | 22/03/24 → … |
Fingerprint
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EFRA
Mutlu, O. (PhD candidate), Fensel, A. (Promotor), Hürriyetoğlu, A. (Co-promotor) & van der Velden, B. (Co-promotor)
1/12/23 → …
Project: PhD
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EU23033 - EFRA (BO-64-101-014)
van der Velden, B. (Project Leader)
1/01/23 → 31/12/23
Project: LVVN project