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

Dataset Card for MetRec

Dataset Summary

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

Supported Tasks and Leaderboards

[More Information Needed]


The dataset is based on Arabic.

Dataset Structure

Data Instances


    >>> {'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.

no split 10,065

Dataset Creation

Curation Rationale

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Source Data

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Initial Data Collection and Normalization

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Who are the source language producers?

[More Information Needed]


Annotation process

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Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

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Considerations for Using the Data

Discussion of Social Impact and Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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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} }


Thanks to @abdulelahsm for adding this dataset.

Models trained or fine-tuned on emotone_ar

None yet