Work

Ahasis Shared Task: Hybrid Lexicon-Augmented AraBERT Model for Sentiment Detection in Arabic Dialects

Year: 2025

Type: conference-paper

Abstract: This work was conducted as part of the Ahasis@RANLP-2025 shared task, which focuses on sentiment detection in Arabic dialects within the hotel review domain.The primary objective is to advance sentiment analysis methodologies tailored to dialectal Arabic.Our work combines data augmentation with a hybrid model that integrates AraBERT and our created sentiment lexicon.Notably, our hybrid model significantly improved performance, reaching an F1-score of 0.74, compared to 0.56 when using only AraBERT.These results highlight the effectiveness of lexicon integration and augmentation strategies in enhancing both the accuracy and robustness of sentiment classification in dialectal Arabic.

DOI: 10.26615/978-954-452-109-7-005

Authors: Shimaa Amer Ibrahim, Mabrouka Bessghaier, Wajdi Zaghouani

Institution: Northwestern University in Qatar

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: Fonds National de la Recherche Luxembourg, Qatar National Research Fund

OpenAlex ID: W7140098543

FWCI: 2.86

Cites:

Cited by: 3

Related to: 10