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From Data to Insights: Constructing and Evaluating a Hospitality Dataset for Quadruple Aspect-Based Sentiment Analysis

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Web Information Systems Engineering – WISE 2024 (WISE 2024)

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Abstract

Recent advances in Quadruple Aspect-Based Sentiment Analysis (Quad-ABSA) have heavily relied on datasets from SemEval challenges, which raises concerns regarding the generalizability of these models across diverse domains. This study addresses this limitation by introducing a novel dataset specifically tailored to the hospitality sector, offering a unique benchmark to evaluate Quad-ABSA models. Our experiments reveal a notable gap: while existing models perform well with SemEval datasets, they fail to maintain their effectiveness when applied to our new domain-specific dataset. This underperformance highlights the critical importance of understanding dataset nuances, including domain-specific characteristics and annotation quality, which significantly influence model performance and generalization. Our research highlights the necessity for broader evaluations of Quad-ABSA models, advocating for the development and utilization of diverse and high-quality datasets to ensure robust and versatile sentiment analysis solutions.

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Notes

  1. 1.

    github.com/marwahalharbi2/QuadABSA-TourismDataset.git.

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Acknowledgments

We are deeply grateful to the Saudi Arabian Cultural Mission in Australia and the Ministry of Education (Saudi Arabia) for their dedicated support and financial assistance, which have been instrumental in making this work possible.

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Authors and Affiliations

  1. Institute for Sustainable Industries and Liveable Cities, Victoria University, Melbourne, VIC, 3011, Australia

    Marwah Alharbi & Yuan Miao

  2. Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, 3086, Australia

    Jiao Yin & Jinli Cao

Authors
  1. Marwah Alharbi
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  2. Jiao Yin
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  3. Yuan Miao
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  4. Jinli Cao
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Correspondence to Jiao Yin .

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Editors and Affiliations

  1. Qatar University, Doha, Qatar

    Mahmoud Barhamgi

  2. Victoria University, Melbourne, VIC, Australia

    Hua Wang

  3. Tianjin University, Tianjin, China

    Xin Wang

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Alharbi, M., Yin, J., Miao, Y., Cao, J. (2025). From Data to Insights: Constructing and Evaluating a Hospitality Dataset for Quadruple Aspect-Based Sentiment Analysis. In: Barhamgi, M., Wang, H., Wang, X. (eds) Web Information Systems Engineering – WISE 2024. WISE 2024. Lecture Notes in Computer Science, vol 15436. Springer, Singapore. https://doi.org/10.1007/978-981-96-0579-8_8

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