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oclar

References:

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:oclar')
  • Description:
The researchers of OCLAR Marwan et al. (2019), they gathered Arabic costumer reviews from Google reviewsa and Zomato website 
(https://www.zomato.com/lebanon) on wide scope of domain, including restaurants, hotels, hospitals, local shops, etc.
The corpus finally contains 3916 reviews in 5-rating scale. For this research purpose, the positive class considers
rating stars from 5 to 3 of 3465 reviews, and the negative class is represented from values of 1 and 2 of about 451 texts.
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'train' 3916
  • Features:
{
    "pagename": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "rating": {
        "dtype": "int8",
        "id": null,
        "_type": "Value"
    }
}