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VIDEO DOI: https://doi.org/10.48448/9p7r-5c95

workshop paper

ACL 2024

August 16, 2024

Bangkok, Thailand

SussexAI at ArAIEval Shared Task: Mitigating Class Imbalance in Arabic Propaganda Detection

keywords:

macro f1.

micro f1

random truncation

propagnanda detection

sequence classification

class imbalance

data augmentation

In this paper, we are exploring mitigating class imbalance in Arabic propaganda detection. Given a multigenre text which could be a news paragraph or a tweet, the objective is to identify the propaganda technique employed in the text along with the exact span(s) where each technique occurs. We approach this task as a sequence tagging task. We utilise AraBERT for sequence classification and implement data augmentation and random truncation methods to mitigate the class imbalance within the dataset. We demonstrate the importance of considering macro-F1 as well as micro-F1 when evaluating classifier performance in this scenario.

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Transcript English (automatic)

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