Work

Team Curie at HSD-2Lang 2024: Hate Speech Detection in Turkish and Arabic Tweets using BERT-based models

Year: 2024

Type: conference-paper

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 1 .

Source: Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)

DOI: 10.18653/v1/2024.case-1.30

Authors: Ehsan Barkhodar, Işık Topçu, Ali Hürriyetoğlu

Institutions: Koç University, Wageningen University & Research

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: European Commission, HORIZON EUROPE European Research Council

Awards: AI-based Data Platform for Fair Social Policies, Extreme Food Risk Analytics, Achieving Ecological Resilient Dynamism for the European food system through consumer-driven policies, socio-ecological challenges, biodiversity, data-driven policy, sustainable futures