Multi-Aspect Sentiment Analysis of Arabic Café Reviews Using Machine and Deep Learning Approaches Article Swipe
This dataset contains 3,000 Arabic café reviews collected from Google Maps in Riyadh, Saudi Arabia. Each review has been manually annotated by three expert annotators, and the final labels were determined through majority voting to ensure reliability. The dataset includes two target variables: aspect category (food, drinks, service, lounge, price) and associated sentiment polarity (positive, negative, neutral). All reviews were cleaned and preprocessed to remove duplicates, personal identifiers, and irrelevant metadata. This dataset supports research in Arabic sentiment analysis, aspect-based sentiment analysis (ABSA), and machine learning applications for real-world consumer intelligence.
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Metadata
- Type
- article
- Landing Page
- https://doi.org/10.5281/zenodo.17781915
- OA Status
- green
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- https://openalex.org/W7108207953
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7108207953Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17781915Digital Object Identifier
- Title
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Multi-Aspect Sentiment Analysis of Arabic Café Reviews Using Machine and Deep Learning ApproachesWork title
- Type
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articleOpenAlex work type
- Publication year
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2025Year of publication
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2025-12-01Full publication date if available
- Authors
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Al-dossari HmoodList of authors in order
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https://doi.org/10.5281/zenodo.17781915Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.5281/zenodo.17781915Direct OA link when available
- Concepts
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Sentiment analysis, Artificial intelligence, Computer science, Natural language processing, Deep learning, Arabic, Voting, Polarity (international relations), Majority rule, Margin (machine learning), Information retrieval, Computational linguisticsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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