Datasets:
labr

Task Categories: text-classification
Languages: ar
Multilinguality: monolingual
Size Categories: 10K<n<100K
Licenses: unknown
Language Creators: found
Annotations Creators: found
Source Datasets: original
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Dataset Card for LABR

Dataset Summary

This dataset contains over 63,000 book reviews in Arabic. It is the largest sentiment analysis dataset for Arabic to-date. The book reviews were harvested from the website Goodreads during the month or March 2013. Each book review comes with the goodreads review id, the user id, the book id, the rating (1 to 5) and the text of the review.

Supported Tasks and Leaderboards

The dataset was published on this paper.

Languages

The dataset is based on Arabic.

Dataset Structure

Data Instances

A typical data point comprises a rating from 1 to 5 where the higher the rating the better the review.

Data Fields

  • text (str): Review text.
  • label (int): Review rating.

Data Splits

The data is split into a training and testing. The split is organized as the following

train test
data split 11,760 2,935

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

downloaded over 220,000 reviews from the book readers social network www.goodreads.com during the month of March 2013

Who are the source language producers?

Reviews.

Annotations

The dataset does not contain any additional annotations.

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@inproceedings{aly2013labr,
  title={Labr: A large scale arabic book reviews dataset},
  author={Aly, Mohamed and Atiya, Amir},
  booktitle={Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  pages={494--498},
  year={2013}
}

Contributions

Thanks to @zaidalyafeai for adding this dataset.

Update on GitHub
Papers with Code

Models trained or fine-tuned on labr