---
language:
- en
license: other
task_categories:
  - tabular-regression
features:
- name: symbols
  dtype: string
- name: datetime
  dtype: string
- name: title
  dtype: string
- name: url
  dtype: string
- name: authors
  dtype: string
- name: summary
  dtype: string
- name: source
  dtype: string
- name: topics
  dtype: string
- name: sentiment
  dtype: string
- name: symbol_sentiment
  dtype: string
extra_gated_prompt: "To get access to this dataset, you must subscribe to Papers With Backtest. To subscribe, go to https://paperswithbacktest.com/ > Login > Choose Your Plan > Subscribe."
---
# Dataset Information

This dataset includes daily rates data for various bonds. 

## Instruments Included

Stocks, ETFs, Forex, Cryptocurrencies, Commodities and more.

## Dataset Columns

- `symbols`: The symbols in the news, typically representing stock tickers or other financial instruments mentioned in the article.
- `datetime`: The date and time when the news article was published, formatted as a string.
- `title`: The title of the news article, providing a brief and descriptive summary of the content.
- `url`: The web address (URL) where the news article is hosted, allowing for direct access to the full text.
- `authors`: The names of the authors who wrote the article, often listed as a comma-separated string if there are multiple authors.
- `summary`: A brief summary or abstract of the article's content, capturing the main points discussed in the news.
- `source`: The name of the media outlet or organization that published the news article, indicating the origin of the information.
- `topics`: The key topics or themes covered in the article, often represented as a comma-separated string of keywords.
- `sentiment`: The overall sentiment of the article's content, typically categorized as positive, negative, or neutral, indicating the tone of the news.
- `symbol_sentiment`: The sentiment associated specifically with the symbols mentioned in the article, reflecting the sentiment toward those financial instruments.

## Data Splits

The data is split into a training set.

## Dataset Maintenance

The dataset is updated on a monthly basis by [Papers With Backtest](https://paperswithbacktest.com).