README.md

metadata

license:
  - cc0-1.0
converted_from: kaggle
kaggle_id: timmayer/covid-news-articles-2020-2022

Dataset Card for COVID News Articles (2020 - 2022)

Table of Contents

• 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: https://kaggle.com/datasets/timmayer/covid-news-articles-2020-2022
• Repository:
• Paper:
• Leaderboard:
• Point of Contact:

Dataset Summary

The dataset encapsulates approximately half a million news articles collected over a period of 2 years during the Coronavirus pandemic onset and surge. It consists of 3 columns - title, content and category. title refers to the headline of the news article. content refers to the article in itself and category denotes the overall context of the news article at a high level. The dataset encapsulates approximately half a million news articles collected over a period of 2 years during the Coronavirus pandemic onset and surge. It consists of 3 columns - title, content and category. title refers to the headline of the news article. content refers to the article in itself and category denotes the overall context of the news article at a high level.

This dataset can be used to pre-train large language models (LLMs) and demonstrate NLP downstream tasks like binary/multi-class text classification. The dataset can be used to study the difference in behaviors of language models when there is a shift in data. For e.g., the classic transformers based BERT model was trained before the COVID era. By training a masked language model (MLM) using this dataset, we can try to differentiate the behaviors of the original BERT model vs the newly trained models.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

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

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

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

This dataset was shared by @timmayer

Licensing Information

The license for this dataset is cc0-1.0

Citation Information

[More Information Needed]

Contributions

[More Information Needed]