Nullpointer at ArAIEval Shared Task: Arabic Propagandist Technique Detection with Token-to-Word Mapping in Sequence Tagging

• URL: http://arxiv.org/abs/2407.01360v1
• Date: Mon, 1 Jul 2024 15:15:24 GMT
• Title: Nullpointer at ArAIEval Shared Task: Arabic Propagandist Technique Detection with Token-to-Word Mapping in Sequence Tagging
• Authors: Abrar Abir, Kemal Oflazer,
• Abstract summary: This paper investigates the optimization of propaganda technique detection in Arabic text, including tweets & news paragraphs, from ArAIEval shared task 1. Experimental results show relying on the first token of the word for technique prediction produces the best performance.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper investigates the optimization of propaganda technique detection in Arabic text, including tweets \& news paragraphs, from ArAIEval shared task 1. Our approach involves fine-tuning the AraBERT v2 model with a neural network classifier for sequence tagging. Experimental results show relying on the first token of the word for technique prediction produces the best performance. In addition, incorporating genre information as a feature further enhances the model's performance. Our system achieved a score of 25.41, placing us 4$^{th}$ on the leaderboard. Subsequent post-submission improvements further raised our score to 26.68.

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