mlsanityData to 14 Oct 2026

AraNet: A Deep Learning Toolkit for Arabic Social Media

arXiv 1912.13072 ↗First posted 30 Dec 2019cs.CL cs.IR cs.LGcited by 14

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Abstract (arXiv)

We describe AraNet, a collection of deep learning Arabic social media processing tools. Namely, we exploit an extensive host of publicly available and novel social media datasets to train bidirectional encoders from transformer models (BERT) to predict age, dialect, gender, emotion, irony, and sentiment. AraNet delivers state-of-the-art performance on a number of the cited tasks and competitively on others. In addition, AraNet has the advantage of being exclusively based on a deep learning framework and hence feature engineering free. To the best of our knowledge, AraNet is the first to performs predictions across such a wide range of tasks for Arabic NLP and thus meets a critical needs. We publicly release AraNet to accelerate research and facilitate comparisons across the different tasks.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Dec 2019.

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Citing papers per year: 2021: 2; 2022: 6; 2023: 4; 2024: 2.

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