Abstract
In an era of widespread digital communication, the challenge of identifying and countering disinformation has become increasingly critical. However, compared to the solutions available in the English language, the resources and strategies for tackling this multifaceted problem in Arabic are relatively scarce. To address this issue, this paper presents our solutions to tasks in ArAIEval 2023. Task 1 focuses on detecting persuasion techniques, while Task 2 centers on disinformation detection within Arabic text. Leveraging a multi-head model architecture, fine-tuning techniques, sequential learning, and innovative activation functions, our contributions significantly enhance persuasion techniques and disinformation detection accuracy. Beyond improving performance, our work fills a critical research gap in content analysis for Arabic, empowering individuals, communities, and digital platforms to combat deceptive content effectively and preserve the credibility of information sources within the Arabic-speaking world.
Original language | English |
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Title of host publication | Proceedings of ArabicNLP 2023 |
Place of Publication | Stroudsburg |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 519-524 |
Number of pages | 6 |
ISBN (Electronic) | 9781959429272 |
DOIs | |
Publication status | Published - 2023 |
Externally published | Yes |
Event | 1st Arabic Natural Language Processing Conference, ArabicNLP 2023 - Hybrid, Singapore, Singapore Duration: 7 Dec 2023 → 7 Dec 2023 |
Conference
Conference | 1st Arabic Natural Language Processing Conference, ArabicNLP 2023 |
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Country/Territory | Singapore |
City | Hybrid, Singapore |
Period | 7/12/23 → 7/12/23 |