Dataset Card for Emotional Tone in Arabic

Dataset Summary

Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The dataset is based on Arabic.

Dataset Structure

Data Instances

example:

    >>> {'label': 0, 'tweet': 'الاوليمبياد الجايه هكون لسه ف الكليه ..'}

Data Fields

• "tweet": plain text tweet in Arabic

• "label": emotion class label

the dataset distribution and balance for each class looks like the following

|label||Label description | Count | |---------|---------| ------- | |0 |none | 1550 | |1 |anger | 1444 | |2 |joy | 1281 | |3 |sadness | 1256 | |4 |love | 1220 | |5 |sympathy | 1062 | |6 |surprise | 1045 | |7 |fear | 1207 |

Data Splits

The dataset is not split.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

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

@inbook{inbook,
author = {Al-Khatib, Amr and El-Beltagy, Samhaa},
year = {2018},
month = {01},
pages = {105-114},
title = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II},
isbn = {978-3-319-77115-1},
doi = {10.1007/978-3-319-77116-8_8}
}

Contributions

Thanks to @abdulelahsm for adding this dataset.