Dataset:

Task Categories: text-classification
Languages: ar
Multilinguality: monolingual
Size Categories: 1K<n<10K
Licenses: unknown
Language Creators: found
Annotations Creators: found
Source Datasets: original

Dataset Card for ArRestReviews

Dataset Summary

Dataset of 8364 restaurant reviews from qaym.com in Arabic for sentiment analysis

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The dataset is based on Arabic.

Dataset Structure

Data Instances

A typical data point comprises of the following:

  • "polarity": which is a string value of either 0 or 1 indicating the sentiment around the review

  • "text": is the review plain text of a restaurant in Arabic

  • "restaurant_id": the restaurant ID on the website

  • "user_id": the user ID on the website

example:

{
    'polarity': 0,  # negative
    'restaurant_id': '1412',
    'text': 'عادي جدا مامن زود',
    'user_id': '21294'
}

Data Fields

  • "polarity": is a string value of either 0 or 1 indicating the sentiment around the review

  • "text": is the review plain text of a restaurant in Arabic

  • "restaurant_id": the restaurant ID on the website (string)

  • "user_id": the user ID on the website (string)

Data Splits

The dataset is not split.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

Contains 8364 restaurant reviews from qaym.com

Who are the source language producers?

From tweeter.

Annotations

The polarity field provides a label of 1 or -1 pertaining to the sentiment of the review

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Discussion of Social Impact and Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@InProceedings{10.1007/978-3-319-18117-2_2, author="ElSahar, Hady and El-Beltagy, Samhaa R.", editor="Gelbukh, Alexander", title="Building Large Arabic Multi-domain Resources for Sentiment Analysis", booktitle="Computational Linguistics and Intelligent Text Processing", year="2015", publisher="Springer International Publishing", address="Cham", pages="23--34", isbn="978-3-319-18117-2" }

Contributions

Thanks to @abdulelahsm for adding this dataset.

Models trained or fine-tuned on ar_res_reviews

None yet