Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
Arabic
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
| 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](khaled.alomari@adu.ac.ae) | |
| ### 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. |