2024
ACL
ACL 2024
SussexAI at ArAIEval Shared Task: Mitigating Class Imbalance in Arabic Propaganda Detection
Abstract
AbstractIn this paper, we are exploring mitigating class imbalancein Arabic propaganda detection. Given amultigenre text which could be a news paragraphor a tweet, the objective is to identify the propagandatechnique employed in the text along withthe exact span(s) where each technique occurs. Weapproach this task as a sequence tagging task. Weutilise AraBERT for sequence classification andimplement data augmentation and random truncationmethods to mitigate the class imbalance withinthe dataset. We demonstrate the importance ofconsidering macro-F1 as well as micro-F1 whenevaluating classifier performance in this scenario.
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio