README.md

metadata

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

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

[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 for adding this dataset.