ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Content

Maram Hasanain, Md. Arid Hasan, Fatema Ahmed, Reem Suwaileh, Md. Rafiul Biswas +2 more
7/5/2024
cs.CLcs.AIcs.CV

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Abstract

We present an overview of the second edition of the ArAIEval shared task, organized as part of the ArabicNLP 2024 conference co-located with ACL 2024. In this edition, ArAIEval offers two tasks: (i) detection of propagandistic textual spans with persuasion techniques identification in tweets and news articles, and (ii) distinguishing between propagandistic and non-propagandistic memes. A total of 14 teams participated in the final evaluation phase, with 6 and 9 teams participating in Tasks 1 and 2, respectively. Finally, 11 teams submitted system description papers. Across both tasks, we observed that fine-tuning transformer models such as AraBERT was at the core of the majority of the participating systems. We provide a description of the task setup, including a description of the dataset construction and the evaluation setup. We further provide a brief overview of the participating systems. All datasets and evaluation scripts are released to the research community (https://araieval.gitlab.io/). We hope this will enable further research on these important tasks in Arabic.

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@article{hasanain2024araieval,
  title  = {ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Content},
  author = {Maram Hasanain and Md. Arid Hasan and Fatema Ahmed and Reem Suwaileh and Md. Rafiul Biswas and Wajdi Zaghouani and Firoj Alam},
  year   = {2024},
  eprint = {2407.04247},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.04247v1}
}

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