README.md

metadata

annotations_creators:
  - found
language_creators:
  - found
language:
  - ar
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
pretty_name: ArRestReviews
dataset_info:
  features:
    - name: polarity
      dtype:
        class_label:
          names:
            '0': negative
            '1': positive
    - name: text
      dtype: string
    - name: restaurant_id
      dtype: string
    - name: user_id
      dtype: string
  splits:
    - name: train
      num_bytes: 3617085
      num_examples: 8364
  download_size: 1887029
  dataset_size: 3617085
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Dataset Card for ArRestReviews

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: Large Arabic Sentiment Analysis Resources
• Repository: Large Arabic Sentiment Analysis Resources
• Paper: Building Large Arabic Multi-domain Resources for Sentiment Analysis
• Point of Contact: hady elsahar

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.