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license: cc-by-nc-nd-4.0
---

# ARACOVID19-SSD: ARABIC COVID-19 SENTIMENT AND SARCASM DETECTION DATASET

## Description

AraCOVID19-SSD is a manually annotated Arabic COVID-19 sarcasm and sentiment detection dataset containing 5,162 tweets. The **labels** used in the dataset are the following:

<div>
    <img src="https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F904283%2Fd463ee4c63a9ad484036a60a30807d8f%2Flabels.JPG?generation=1759523079401255&alt=media" alt="AraCOVID19-SSD Sarcasm and Sentiment Labels">
</div>

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## Examples

Examples of the instances from the dataset are provided in the below Table:

<div>
    <img src="https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F904283%2F1baa73df13f820a0e9131e2a9e6c4c47%2Fexamples.JPG?generation=1759523100398116&alt=media" alt="Example tweets and their annotations from AraCOVID19-SSD">
</div>

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## Statistics

The statistics **for** the dataset are provided in the below Table:

<div>
    <img src="https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F904283%2F4b8d4e74985d39a374a86fe4ad63abc8%2FstatsJPG.JPG?generation=1759523117721681&alt=media" alt="Statistical distribution of Sarcasm and Sentiment labels">
</div>

## Citations
If you want to use the dataset please cite the following arXiv paper:


```
@article{ameur2021aracovid19,
  title={Aracovid19-ssd: Arabic covid-19 sentiment and sarcasm detection dataset},
  author={Ameur, Mohamed Seghir Hadj and Aliane, Hassina},
  journal={arXiv preprint arXiv:2110.01948},
  year={2021}
}
```

## Contacts:
For all questions please contact ``mohamedhadjameur@gmail.com``