
# Dataset Card for Emotional Tone in Arabic

## Table of Contents
- [Dataset Card for Emotional Tone in Arabic](#dataset-card-for-emotional-tone-in-arabic)
  - [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:** [Repository](https://github.com/AmrMehasseb/Emotional-Tone)
- **Paper:** [Emotional Tone Detection in Arabic Tweets](https://www.researchgate.net/publication/328164296_Emotional_Tone_Detection_in_Arabic_Tweets_18th_International_Conference_CICLing_2017_Budapest_Hungary_April_17-23_2017_Revised_Selected_Papers_Part_II)
- **Point of Contact:** [Amr Al-Khatib](https://github.com/AmrMehasseb)

### 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. 

|          |   train |
|----------|--------:|
| no split |  10,065 |

## 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](https://github.com/abdulelahsm) for adding this dataset.
task_categories:text-classification task_ids:sentiment-classification annotations_creators:found language_creators:found multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:ar license:unknown region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["ar"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pretty_name": "Emotional Tone in Arabic", "dataset_info": {"features": [{"name": "tweet", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "none", "1": "anger", "2": "joy", "3": "sadness", "4": "love", "5": "sympathy", "6": "surprise", "7": "fear"}}}}], "splits": [{"name": "train", "num_bytes": 1541746, "num_examples": 10065}], "download_size": 1563138, "dataset_size": 1541746}}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Arabic #license-unknown #region-us 

Dataset Card for Emotional Tone in Arabic
=========================================


Table of Contents
-----------------


* Dataset Card for Emotional Tone in Arabic
	+ Table of Contents
	+ Dataset Description
		- Dataset Summary
		- Supported Tasks and Leaderboards
		- Languages
	+ Dataset Structure
		- Data Instances
		- Data Fields
		- Data Splits
	+ |split|num examples|
	+ Dataset Creation
		- Curation Rationale
		- Source Data
			* Initial Data Collection and Normalization
			* Who are the source language producers?
		- Annotations
			* Annotation process
			* Who are the annotators?
		- Personal and Sensitive Information
	+ Considerations for Using the Data
		- Social Impact of Dataset
		- Discussion of Biases
		- Other Known Limitations
	+ Additional Information
		- Dataset Curators
		- Licensing Information
		- Citation Information
		- Contributions


Dataset Description
-------------------


* Repository: Repository
* Paper: Emotional Tone Detection in Arabic Tweets
* Point of Contact: Amr Al-Khatib


### Dataset Summary


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


### Supported Tasks and Leaderboards


### Languages


The dataset is based on Arabic.


Dataset Structure
-----------------


### Data Instances


example:


### 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


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions


Thanks to @abdulelahsm for adding this dataset.



### Dataset Summary


Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text ### Supported Tasks and Leaderboards ### Languages


The dataset is based on Arabic.


Dataset Structure
----------------- ### Data Instances


example: ### 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 ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @abdulelahsm for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Arabic #license-unknown #region-us 
 ### Dataset Summary


Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text ### Supported Tasks and Leaderboards ### Languages


The dataset is based on Arabic.


Dataset Structure
----------------- ### Data Instances


example: ### 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 ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @abdulelahsm for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Arabic #license-unknown #region-us 
### Dataset Summary


Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text### Supported Tasks and Leaderboards### Languages


The dataset is based on Arabic.


Dataset Structure
-----------------### Data Instances


example:### 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### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------### Social Impact of Dataset### Discussion of Biases### Other Known Limitations


Additional Information
----------------------### Dataset Curators### Licensing Information### Contributions


Thanks to @abdulelahsm for adding this dataset.