AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects

Maram Alharbi; Salmane Chafik; Saad Ezzini; Ruslan Mitkov; Tharindu Ranasinghe; Hansi Hettiarachchi

doi:10.26615/978-954-452-109-7-001

AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects

Maram Alharbi
, Salmane Chafik
, Saad Ezzini
, Ruslan Mitkov
, Tharindu Ranasinghe
, Hansi Hettiarachchi

Department of Information and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

The hospitality industry in the Arab world increasingly relies on customer feedback to shape services, driving the need for advanced Arabic sentiment analysis tools. To address this challenge, the Sentiment Analysis on Arabic Dialects in the Hospitality Domain shared task focuses on Sentiment Detection in Arabic Dialects. This task leverages a multi-dialect, manually curated dataset derived from hotel reviews originally written in Modern Standard Arabic (MSA) and translated into Saudi and Moroccan (Darija) dialects. The dataset consists of 538 sentiment-balanced reviews spanning positive, neutral, and negative categories. Translations were validated by native speakers to ensure dialectal accuracy and sentiment preservation. This resource supports the development of dialect-aware NLP systems for real-world applications in customer experience analysis. More than 40 teams have registered for the shared task, with 12 submitting systems during the evaluation phase. The top-performing system achieved an F1 score of 0.81, demonstrating the feasibility and ongoing challenges of sentiment analysis across Arabic dialects.

Original language	English
Title of host publication	AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain
Subtitle of host publication	A Multi-Dialect Benchmark, associated with the 15th International Conference on Recent Advances in Natural Language Processing, RANLP 2025
Editors	Maram I. Alharbi, Salmane Chafik, Saad Ezzini, Ruslan Mitkov, Tharindu Ranasinghe, Hansi Hettiarachchi
Publisher	Incoma Ltd
Pages	1-6
Number of pages	6
ISBN (Electronic)	9789544521097
DOIs	https://doi.org/10.26615/978-954-452-109-7-001
State	Published - 2025
Event	2025 Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, AHaSIS-ST 2025 - Varna, Bulgaria Duration: 12 Sep 2025 → 12 Sep 2025

Publication series

Name	International Conference Recent Advances in Natural Language Processing, RANLP
ISSN (Print)	1313-8502

Conference

Conference	2025 Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, AHaSIS-ST 2025
Country/Territory	Bulgaria
City	Varna
Period	12/09/25 → 12/09/25

Bibliographical note

Publisher Copyright:
© 2025 Incoma Ltd. All rights reserved.

ASJC Scopus subject areas

Software
Computer Science Applications
Artificial Intelligence
Electrical and Electronic Engineering

Access to Document

10.26615/978-954-452-109-7-001

Cite this

Alharbi, M., Chafik, S., Ezzini, S., Mitkov, R., Ranasinghe, T., & Hettiarachchi, H. (2025). AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects. In M. I. Alharbi, S. Chafik, S. Ezzini, R. Mitkov, T. Ranasinghe, & H. Hettiarachchi (Eds.), AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, associated with the 15th International Conference on Recent Advances in Natural Language Processing, RANLP 2025 (pp. 1-6). (International Conference Recent Advances in Natural Language Processing, RANLP). Incoma Ltd. https://doi.org/10.26615/978-954-452-109-7-001

Alharbi, Maram ; Chafik, Salmane ; Ezzini, Saad et al. / AHaSIS : Shared Task on Sentiment Analysis for Arabic Dialects. AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, associated with the 15th International Conference on Recent Advances in Natural Language Processing, RANLP 2025. editor / Maram I. Alharbi ; Salmane Chafik ; Saad Ezzini ; Ruslan Mitkov ; Tharindu Ranasinghe ; Hansi Hettiarachchi. Incoma Ltd, 2025. pp. 1-6 (International Conference Recent Advances in Natural Language Processing, RANLP).

@inproceedings{c4d6bbd2bc0940e79abff37d3a30a03e,

title = "AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects",

abstract = "The hospitality industry in the Arab world increasingly relies on customer feedback to shape services, driving the need for advanced Arabic sentiment analysis tools. To address this challenge, the Sentiment Analysis on Arabic Dialects in the Hospitality Domain shared task focuses on Sentiment Detection in Arabic Dialects. This task leverages a multi-dialect, manually curated dataset derived from hotel reviews originally written in Modern Standard Arabic (MSA) and translated into Saudi and Moroccan (Darija) dialects. The dataset consists of 538 sentiment-balanced reviews spanning positive, neutral, and negative categories. Translations were validated by native speakers to ensure dialectal accuracy and sentiment preservation. This resource supports the development of dialect-aware NLP systems for real-world applications in customer experience analysis. More than 40 teams have registered for the shared task, with 12 submitting systems during the evaluation phase. The top-performing system achieved an F1 score of 0.81, demonstrating the feasibility and ongoing challenges of sentiment analysis across Arabic dialects.",

author = "Maram Alharbi and Salmane Chafik and Saad Ezzini and Ruslan Mitkov and Tharindu Ranasinghe and Hansi Hettiarachchi",

note = "Publisher Copyright: {\textcopyright} 2025 Incoma Ltd. All rights reserved.; 2025 Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, AHaSIS-ST 2025 ; Conference date: 12-09-2025 Through 12-09-2025",

year = "2025",

doi = "10.26615/978-954-452-109-7-001",

language = "English",

series = "International Conference Recent Advances in Natural Language Processing, RANLP",

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booktitle = "AHaSIS-ST\_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain",

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Alharbi, M, Chafik, S, Ezzini, S, Mitkov, R, Ranasinghe, T & Hettiarachchi, H 2025, AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects. in MI Alharbi, S Chafik, S Ezzini, R Mitkov, T Ranasinghe & H Hettiarachchi (eds), AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, associated with the 15th International Conference on Recent Advances in Natural Language Processing, RANLP 2025. International Conference Recent Advances in Natural Language Processing, RANLP, Incoma Ltd, pp. 1-6, 2025 Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, AHaSIS-ST 2025, Varna, Bulgaria, 12/09/25. https://doi.org/10.26615/978-954-452-109-7-001

AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects. / Alharbi, Maram; Chafik, Salmane; Ezzini, Saad et al.
AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, associated with the 15th International Conference on Recent Advances in Natural Language Processing, RANLP 2025. ed. / Maram I. Alharbi; Salmane Chafik; Saad Ezzini; Ruslan Mitkov; Tharindu Ranasinghe; Hansi Hettiarachchi. Incoma Ltd, 2025. p. 1-6 (International Conference Recent Advances in Natural Language Processing, RANLP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Alharbi, Maram

AU - Chafik, Salmane

AU - Ezzini, Saad

AU - Mitkov, Ruslan

AU - Ranasinghe, Tharindu

AU - Hettiarachchi, Hansi

PY - 2025

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N2 - The hospitality industry in the Arab world increasingly relies on customer feedback to shape services, driving the need for advanced Arabic sentiment analysis tools. To address this challenge, the Sentiment Analysis on Arabic Dialects in the Hospitality Domain shared task focuses on Sentiment Detection in Arabic Dialects. This task leverages a multi-dialect, manually curated dataset derived from hotel reviews originally written in Modern Standard Arabic (MSA) and translated into Saudi and Moroccan (Darija) dialects. The dataset consists of 538 sentiment-balanced reviews spanning positive, neutral, and negative categories. Translations were validated by native speakers to ensure dialectal accuracy and sentiment preservation. This resource supports the development of dialect-aware NLP systems for real-world applications in customer experience analysis. More than 40 teams have registered for the shared task, with 12 submitting systems during the evaluation phase. The top-performing system achieved an F1 score of 0.81, demonstrating the feasibility and ongoing challenges of sentiment analysis across Arabic dialects.

AB - The hospitality industry in the Arab world increasingly relies on customer feedback to shape services, driving the need for advanced Arabic sentiment analysis tools. To address this challenge, the Sentiment Analysis on Arabic Dialects in the Hospitality Domain shared task focuses on Sentiment Detection in Arabic Dialects. This task leverages a multi-dialect, manually curated dataset derived from hotel reviews originally written in Modern Standard Arabic (MSA) and translated into Saudi and Moroccan (Darija) dialects. The dataset consists of 538 sentiment-balanced reviews spanning positive, neutral, and negative categories. Translations were validated by native speakers to ensure dialectal accuracy and sentiment preservation. This resource supports the development of dialect-aware NLP systems for real-world applications in customer experience analysis. More than 40 teams have registered for the shared task, with 12 submitting systems during the evaluation phase. The top-performing system achieved an F1 score of 0.81, demonstrating the feasibility and ongoing challenges of sentiment analysis across Arabic dialects.

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DO - 10.26615/978-954-452-109-7-001

M3 - Conference contribution

AN - SCOPUS:105034486943

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A2 - Chafik, Salmane

A2 - Ezzini, Saad

A2 - Mitkov, Ruslan

A2 - Ranasinghe, Tharindu

A2 - Hettiarachchi, Hansi

PB - Incoma Ltd

Y2 - 12 September 2025 through 12 September 2025

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Alharbi M, Chafik S, Ezzini S, Mitkov R, Ranasinghe T, Hettiarachchi H. AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects. In Alharbi MI, Chafik S, Ezzini S, Mitkov R, Ranasinghe T, Hettiarachchi H, editors, AHaSIS-ST_2025 - Proceedings of the Shared Task on Sentiment Analysis on Arabic Dialects in the Hospitality Domain: A Multi-Dialect Benchmark, associated with the 15th International Conference on Recent Advances in Natural Language Processing, RANLP 2025. Incoma Ltd. 2025. p. 1-6. (International Conference Recent Advances in Natural Language Processing, RANLP). doi: 10.26615/978-954-452-109-7-001

AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

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