TY - GEN
T1 - Enhancing Arabic Dialectal Sentiment Analysis through Advanced Data Augmentation Techniques
AU - Biswas, Md Rafiul
AU - Zaghouani, Wajdi
N1 - Publisher Copyright:
© 2025 Incoma Ltd. All rights reserved.
PY - 2025/9
Y1 - 2025/9
N2 - This work addresses the challenge of Arabic sentiment analysis in the hospitality domain in all dialects by using data augmentation techniques. We created a pipeline with three simple techniques: context-based paraphrasing, pattern-based sentence generation, and domain-specific word replacement. Our method preserves the original dialect features, meanings, and key classification details while adding diversity to the training data. It also includes automatic fallback between methods to handle challenges effectively. We used the Fanar API for dialectal data augmentation in the hospitality domain. The AraBERT-Large-v02 model was fine-tuned on original and augmented data, showing improved performance. This study helps solve the problem of limited dialect data in Arabic NLP and offers an effective framework that is useful for other Arabic text analysis tasks.
AB - This work addresses the challenge of Arabic sentiment analysis in the hospitality domain in all dialects by using data augmentation techniques. We created a pipeline with three simple techniques: context-based paraphrasing, pattern-based sentence generation, and domain-specific word replacement. Our method preserves the original dialect features, meanings, and key classification details while adding diversity to the training data. It also includes automatic fallback between methods to handle challenges effectively. We used the Fanar API for dialectal data augmentation in the hospitality domain. The AraBERT-Large-v02 model was fine-tuned on original and augmented data, showing improved performance. This study helps solve the problem of limited dialect data in Arabic NLP and offers an effective framework that is useful for other Arabic text analysis tasks.
UR - https://www.scopus.com/pages/publications/105034468849
U2 - 10.26615/978-954-452-109-7-004
DO - 10.26615/978-954-452-109-7-004
M3 - Conference contribution
AN - SCOPUS:105034468849
T3 - International Conference Recent Advances in Natural Language Processing, RANLP
SP - 24
EP - 28
BT - AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain
A2 - Alharbi, Maram I.
A2 - Chafik, Salmane
A2 - Ezzini, Saad
A2 - Mitkov, Ruslan
A2 - Ranasinghe, Tharindu
A2 - Hettiarachchi, Hansi
PB - Incoma Ltd
T2 - 2025 Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, AHaSIS-ST 2025
Y2 - 12 September 2025 through 12 September 2025
ER -