README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - ar
multilinguality:
  - monolingual
size_categories:
  - 1M<n<10M
source_datasets:
  - original
task_categories:
  - other
task_ids: []
paperswithcode_id: arcov-19
pretty_name: ArCOV19
tags:
  - data-mining
dataset_info:
  config_name: ar_cov19
  features:
    - name: tweetID
      dtype: string
  splits:
    - name: train
      num_bytes: 72223634
      num_examples: 3140158
  download_size: 23678407
  dataset_size: 72223634

Dataset Card for ArCOV19

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage:
• Repository: https://gitlab.com/bigirqu/ArCOV-19
• Paper: ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks
• Leaderboard: [More Information Needed]
• Point of Contact: Fatima Haouari

Dataset Summary

ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 5th of May 2021. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pandemic that includes about 3.2M tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and-liked). The propagation networks include both retweets and conversational threads (i.e., threads of replies). ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others. Preliminary analysis shows that ArCOV-19 captures rising discussions associated with the first reported cases of the disease as they appeared in the Arab world. In addition to the source tweets and the propagation networks, we also release the search queries and the language-independent crawler used to collect the tweets to encourage the curation of similar datasets.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

Arabic

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

tweet_id: the Twitter assigned ID for the tweet object.

Data Splits

[More Information Needed]

Dataset Creation

The dataset collection approach is presented in the following paper: ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

No annotation was provided with the dataset.

Annotation process

No annotation was provided with the dataset.

Who are the annotators?

No annotation was provided with the dataset.

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

Team: bigIR from Qatar University (@bigIR_group)

• Fatima Haouari
• Maram Hasanain
• Reem Suwaileh
• Dr. Tamer Elsayed

Licensing Information

[More Information Needed]

Citation Information

@article{haouari2020arcov19,
      title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},
      author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},
      year={2021},
      eprint={2004.05861},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Contributions

Thanks to @Fatima-Haouari for adding this dataset.