Datasets:
annotations_creators:
- found
language_creators:
- found
languages:
- ar
licenses:
- unknown
multilinguality:
- monolingual
size_categories:
- 1k<n<10k
source_datasets:
- original
task_categories:
- text_classification
task_ids:
- sentiment-classification
Dataset Card for MetRec
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: AJGT
- Repository: AJGT
- Paper: Arabic Tweets Sentimental Analysis Using Machine Learning
- Point of Contact: Khaled Alomari
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.
Languages
The dataset is based on Arabic.
Dataset Structure
Data Instances
A binary datset with with negative and positive sentiments.
Data Fields
[More Information Needed]
Data Splits
The dataset is not split.
| Tain | |
|---|---|
| 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
Discussion of Social Impact and Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
[More Information Needed]
Contributions
Thanks to @zaidalyafeai, @lhoestq for adding this dataset.