Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Arabic
Size:
100K<n<1M
Tags:
License:
Update files from the datasets library (from 1.17.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.17.0
README.md
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---
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# Dataset Card for
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## Table of Contents
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## Dataset Description
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- **Repository:** [AJGT](https://github.com/komari6/Arabic-twitter-corpus-AJGT)
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- **Paper:** [Arabic Tweets Sentimental Analysis Using Machine Learning](https://link.springer.com/chapter/10.1007/978-3-319-60042-0_66)
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- **Point of Contact:** [Khaled Alomari](khaled.alomari@adu.ac.ae)
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### Data Fields
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### Data Splits
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## Considerations for Using the Data
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###
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[More Information
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### Other Known Limitations
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[More Information
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## Additional Information
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### Citation Information
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### Contributions
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task_ids:
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- sentiment-classification
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pretty_name: Arabic Jordanian General Tweets
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# Dataset Card for Arabic Jordanian General Tweets
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## Table of Contents
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- [Dataset Card for Arabic Jordanian General Tweets](#dataset-card-for-arabic-jordanian-general-tweets)
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [|split|num examples|](#splitnum-examples)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
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- [Who are the source language producers?](#who-are-the-source-language-producers)
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- [Annotations](#annotations)
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- [Annotation process](#annotation-process)
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- [Who are the annotators?](#who-are-the-annotators)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Repository:** [Arabic Jordanian General Tweets](https://github.com/komari6/Arabic-twitter-corpus-AJGT)
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- **Paper:** [Arabic Tweets Sentimental Analysis Using Machine Learning](https://link.springer.com/chapter/10.1007/978-3-319-60042-0_66)
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- **Point of Contact:** [Khaled Alomari](khaled.alomari@adu.ac.ae)
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### Data Fields
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- `text` (str): Tweet text.
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- `label` (int): Sentiment.
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### Data Splits
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## Considerations for Using the Data
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### Social Impact of Dataset
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[Needs More Information]
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### Discussion of Biases
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[Needs More Information]
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### Other Known Limitations
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[Needs More Information]
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## Additional Information
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### Citation Information
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```
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@inproceedings{alomari2017arabic,
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title={Arabic tweets sentimental analysis using machine learning},
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author={Alomari, Khaled Mohammad and ElSherif, Hatem M and Shaalan, Khaled},
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booktitle={International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems},
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pages={602--610},
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year={2017},
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organization={Springer}
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}
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```
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### Contributions
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