ArSen-20

Sentiment detection remains a pivotal task in natural language processing, yet its development in Arabic lags due to a scarcity of training materials compared to English. Addressing this gap, we present ArSen-20, a benchmark dataset tailored to propel Arabic sentiment detection forward. ArSen-20 comprises 20,000 professionally labeled tweets sourced from Twitter, focusing on the theme of COVID-19 and spanning the period from 2020 to 2023. Beyond tweet content, the dataset incorporates metadata associated with the user, enriching the contextual understanding. ArSen-20 offers a comprehensive resource to foster advancements in Arabic sentiment analysis and facilitate research in this critical domain.

The ArSen-20 dataset statistics:

| Statistics   |   Num  | 
|:-------------:|:-----:|
| Training set size | 16000 |
| Validation set size| 2000 |
| Testing set size | 2000 |
| Neutral | 17262 |
| Positive | 878 |
| Negative | 1860 |

## Features
The dataset has the following features:

| Field   |  Type  |  Description  |
|:-----------:| :--------: |:----------------: |
| tweet id     | string     | The unique identifier of the requested Tweet.     |
| label   | string     | Sentiment Classification of this tweet.     |
| author id   | string    |The unique identifier of this user.     |
| created_at  | data     | Creation time of the Tweet.    |
| lang  | string     | Language of the Tweet, if detected by Twitter.    |
| like_count  | int     |The number of likes on this tweet.|
|quote_count  | int    | The number of times this tweet has been quoted.    |
| reply_count   | int     | The number of replies to this tweet.    |
| retweet_count| int    | The number of retweets to this tweet.    |
| tweet   | string     | The actual UTF-8 text of the Tweet.    |
|user_verified  | boolean     | Indicates if this user is a verified Twitter User.     |
|followers_count  | int     |The number of followers of the author.     |
| following_count  | int     | The number of following of the author.    |
| tweet_count  | int     | Total number of tweets by the author.    |
| listed_count | int     |The number of public lists that this user is a member of.    |
|name | string     | The name of the user.    |
| username   | string     | The Twitter screen name, handle, or alias.    |
| user_created_at| data     | The UTC datetime that the user account was created.     |
| description  | string     | The text of this user’s profile description (bio).     |

## DownLoad
You can download the dataset from [here](https://github.com/123fangyang/ArSen-20/tree/main/data).

+ ArSen-20_publish.csv - Contains all features.

+ ArSen-20_id_only.csv - Contains only tweets and their author's id.


## Citation
If you use this dataset in your research, please cite the following papers:
```bibtex
@inproceedings{fang2024arsen,
title={ArSen-20: A New Benchmark for Arabic Sentiment Detection},
author={Yang Fang and Cheng Xu},
booktitle={5th Workshop on African Natural Language Processing},
year={2024},
url={https://openreview.net/forum?id=GgsRUF5kJt}
}
```

```bibtex
@inproceedings{fang2024advancing,
    title = "Advancing {A}rabic Sentiment Analysis: {A}r{S}en Benchmark and the Improved Fuzzy Deep Hybrid Network",
    author = "Fang, Yang  and
      Xu, Cheng  and
      Guan, Shuhao  and
      Yan, Nan  and
      Mei, Yuke",
    editor = "Barak, Libby  and
      Alikhani, Malihe",
    booktitle = "Proceedings of the 28th Conference on Computational Natural Language Learning",
    month = nov,
    year = "2024",
    address = "Miami, FL, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.conll-1.39",
    pages = "507--516",
}
```

## contact
If you have any questions or comments about the dataset, please contact Yang Fang (20211209024@chnu.edu.cn).

Potential cooperation in related fields is also welcome. :)

Introducing paper: ArSen-20: A New Benchmark for Arabic Sentiment Detection