8,364 Arabic restaurant reviews from qaym.com labeled for binary sentiment analysis. Each entry includes the raw review text and a corresponding polarity label of 0 or 1.
Use Cases
- Train a binary sentiment classifier using the text and polarity columns to detect customer satisfaction
- Conduct dialectal Arabic NLP research on the informal language used in the text field
- Benchmark Arabic-specific text classification models on restaurant-domain data
Strengths
- 8,364 rows of Arabic-language restaurant feedback
- Binary sentiment labels (0 or 1) stored in the polarity column
- Source data originates from the specialized regional review site qaym.com