komari6/ajgt_twitter_ar

---
annotations_creators:
- found
language_creators:
- found
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: Arabic Jordanian General Tweets
dataset_info:
config_name: plain_text
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': Negative
'1': Positive
splits:
- name: train
num_bytes: 175420
num_examples: 1800
download_size: 91857
dataset_size: 175420
configs:
- config_name: plain_text
data_files:
- split: train
path: plain_text/train-*
default: true
---

# Dataset Card for Arabic Jordanian General Tweets

## Table of Contents
- [Dataset Card for Arabic Jordanian General Tweets](#dataset-card-for-arabic-jordanian-general-tweets)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [|split|num examples|](#splitnum-examples)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
- [Who are the source language producers?](#who-are-the-source-language-producers)
- [Annotations](#annotations)
- [Annotation process](#annotation-process)
- [Who are the annotators?](#who-are-the-annotators)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Repository:** [Arabic Jordanian General Tweets](https://github.com/komari6/Arabic-twitter-corpus-AJGT)
- **Paper:** [Arabic Tweets Sentimental Analysis Using Machine Learning](https://link.springer.com/chapter/10.1007/978-3-319-60042-0_66)
- **Point of Contact:** [Khaled Alomari]([e-mail])

### 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](https://link.springer.com/chapter/10.1007/978-3-319-60042-0_66).

### 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](https://github.com/zaidalyafeai), [@lhoestq](https://github.com/lhoestq) for adding this dataset.

原始信息汇总

数据集概述

数据集名称

• 名称: Arabic Jordanian General Tweets

数据集描述

• 语言: 阿拉伯语
• 许可证: 未知
• 多语言性: 单语种
• 大小类别: 1K<n<10K
• 源数据集: 原始数据
• 任务类别: 文本分类
• 任务ID: 情感分类

数据集结构

• 数据实例: 二分类数据集，包含负面和正面情感
• 数据字段:
  • text (字符串): 推文文本
  • label (整数): 情感标签，其中 0: Negative, 1: Positive
• 数据分割:
  • train: 1800个样本

数据集创建

• 源数据:
  • 初始数据收集和规范化: 包含1800条从Twitter收集的推文
  • 源语言生产者: 来自Twitter
• 注释:
  • 注释过程: 信息不足
  • 注释者: 信息不足

使用数据集的考虑

• 社会影响: 信息不足
• 偏见讨论: 信息不足
• 其他已知限制: 信息不足

附加信息

• 数据集创建者: 信息不足

• 许可证信息: 信息不足

• 引用信息:

  @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} }

• 贡献者: @zaidalyafeai, @lhoestq