Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Arabic
Size:
1K - 10K
License:
{ | |
"plain_text": { | |
"description": "Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect.\n", | |
"citation": "@inproceedings{alomari2017arabic,\n title={Arabic tweets sentimental analysis using machine learning},\n author={Alomari, Khaled Mohammad and ElSherif, Hatem M and Shaalan, Khaled},\n booktitle={International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems},\n pages={602--610},\n year={2017},\n organization={Springer}\n}\n", | |
"homepage": "https://github.com/komari6/Arabic-twitter-corpus-AJGT", | |
"license": "", | |
"features": { | |
"text": { | |
"dtype": "string", | |
"_type": "Value" | |
}, | |
"label": { | |
"names": [ | |
"Negative", | |
"Positive" | |
], | |
"_type": "ClassLabel" | |
} | |
}, | |
"task_templates": [ | |
{ | |
"task": "text-classification", | |
"label_column": "label" | |
} | |
], | |
"builder_name": "parquet", | |
"dataset_name": "ajgt_twitter_ar", | |
"config_name": "plain_text", | |
"version": { | |
"version_str": "1.0.0", | |
"major": 1, | |
"minor": 0, | |
"patch": 0 | |
}, | |
"splits": { | |
"train": { | |
"name": "train", | |
"num_bytes": 175420, | |
"num_examples": 1800, | |
"dataset_name": null | |
} | |
}, | |
"download_size": 91857, | |
"dataset_size": 175420, | |
"size_in_bytes": 267277 | |
} | |
} |