Dataset Card for Arabic Jordanian General Tweets

Dataset Summary

Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect.

Supported Tasks and Leaderboards

The dataset was published on this paper.

Languages

The dataset is based on Arabic.

Dataset Structure

Data Instances

A binary datset with with negative and positive sentiments.

Data Fields

text (str): Tweet text.
label (int): Sentiment.

Data Splits

The dataset is not split.

	train
no split	1,800

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

Contains 1,800 tweets collected from twitter.

Who are the source language producers?

From tweeter.

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{alomari2017arabic,
  title={Arabic tweets sentimental analysis using machine learning},
  author={Alomari, Khaled Mohammad and ElSherif, Hatem M and Shaalan, Khaled},
  booktitle={International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems},
  pages={602--610},
  year={2017},
  organization={Springer}
}

Contributions

Thanks to @zaidalyafeai, @lhoestq for adding this dataset.