Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Arabic
Size:
1K<n<10K
Tags:
License:
File size: 3,356 Bytes
8b735a8 6e53ec0 8b735a8 6e53ec0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 |
---
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-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Discussion of Social Impact and Biases](#discussion-of-social-impact-and-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
- **Homepage:** [AJGT](https://github.com/komari6/Arabic-twitter-corpus-AJGT)
- **Repository:** [AJGT](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
[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](https://github.com/zaidalyafeai), [@lhoestq](https://github.com/lhoestq) for adding this dataset. |