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        <title>A Hybrid Transformer-Based Model for Sentiment Analysis of Arabic Dialect Hotel Reviews</title>
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    <name type="personal">
        <namePart type="given">Rawand</namePart>
        <namePart type="family">Alfugaha</namePart>
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    <name type="personal">
        <namePart type="given">Mohammad</namePart>
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            <title>Proceedings of the Shared Task on Sentiment Analysis for Arabic Dialects</title>
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        <name type="personal">
            <namePart type="given">Maram</namePart>
            <namePart type="family">Alharbi</namePart>
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        <name type="personal">
            <namePart type="given">Salmane</namePart>
            <namePart type="family">Chafik</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Saad</namePart>
            <namePart type="family">Ezzini</namePart>
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        <name type="personal">
            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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            <namePart type="family">Ranasinghe</namePart>
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        <name type="personal">
            <namePart type="given">Hansi</namePart>
            <namePart type="family">Hettiarachchi</namePart>
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            <publisher>INCOMA Ltd., Shoumen, Bulgaria</publisher>
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    <abstract>This paper describes the AraNLP system developed for the “Ahasis” shared task on sentiment detection in Arabic dialects for hotel reviews. The task involved classifying the overall sentiment of hotel reviews (Positive, Negative, or Neutral) written in Arabic dialects, specifically Saudi and Darija. Our proposed model, AraNLP, is a hybrid deep learning classifier that leverages the strengths of a transformer-based Arabic model (AraELECTRA)augmented with classical bag-of-words style features (TF-IDF). Our system achieved an F1-score of 76%, securing the 5th rank in the shared task, significantly outperforming the baseline system’s F1-score of 56%.</abstract>
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%0 Conference Proceedings
%T A Hybrid Transformer-Based Model for Sentiment Analysis of Arabic Dialect Hotel Reviews
%A Alfugaha, Rawand
%A AL-Smadi, Mohammad
%Y Alharbi, Maram
%Y Chafik, Salmane
%Y Ezzini, Saad
%Y Mitkov, Ruslan
%Y Ranasinghe, Tharindu
%Y Hettiarachchi, Hansi
%S Proceedings of the Shared Task on Sentiment Analysis for Arabic Dialects
%D 2025
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F alfugaha-al-smadi-2025-hybrid
%X This paper describes the AraNLP system developed for the “Ahasis” shared task on sentiment detection in Arabic dialects for hotel reviews. The task involved classifying the overall sentiment of hotel reviews (Positive, Negative, or Neutral) written in Arabic dialects, specifically Saudi and Darija. Our proposed model, AraNLP, is a hybrid deep learning classifier that leverages the strengths of a transformer-based Arabic model (AraELECTRA)augmented with classical bag-of-words style features (TF-IDF). Our system achieved an F1-score of 76%, securing the 5th rank in the shared task, significantly outperforming the baseline system’s F1-score of 56%.
%U https://aclanthology.org/2025.ranlp-ahasis.10/
%P 62-68

Markdown (Informal)

[A Hybrid Transformer-Based Model for Sentiment Analysis of Arabic Dialect Hotel Reviews](https://aclanthology.org/2025.ranlp-ahasis.10/) (Alfugaha & AL-Smadi, RANLP 2025)

• A Hybrid Transformer-Based Model for Sentiment Analysis of Arabic Dialect Hotel Reviews (Alfugaha & AL-Smadi, RANLP 2025)

ACL

• Rawand Alfugaha and Mohammad AL-Smadi. 2025. A Hybrid Transformer-Based Model for Sentiment Analysis of Arabic Dialect Hotel Reviews. In Proceedings of the Shared Task on Sentiment Analysis for Arabic Dialects, pages 62–68, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.