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FNSPID: A Comprehensive Financial News Dataset in Time Series

Description

FNSPID is a meticulously curated dataset designed to support research and applications in the field of financial news analysis within the context of time-series forecasting. Our dataset encompasses a wide range of financial news articles, providing a rich resource for developing and testing models aimed at understanding market trends, investor sentiment, and other critical financial indicators.

Link to Github Program

Key Features

  • Extensive Coverage: The dataset contains over 10 million entries, offering broad insights into the financial news landscape.
  • Time-Series Analysis Ready: Organized in a time-series format, FNSPID is ideal for forecasting financial market movements and trends.
  • Diverse Applications: Suitable for various tasks including sentiment analysis, market prediction, and trend analysis.

Citation

If you use the FNSPID dataset in your research, please cite our work as follows:

@misc{dong2024fnspid,
  title={FNSPID: A Comprehensive Financial News Dataset in Time Series},
  author={Zihan Dong and Xinyu Fan and Zhiyuan Peng},
  year={2024},
  eprint={2402.06698},
  archivePrefix={arXiv},
  primaryClass={q-fin.ST}
}

License

This dataset is available under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC-4.0) license. The use of this dataset for commercial purposes is strictly prohibited without prior authorization.

Prohibition of Commercial Use

Commercial use of this code or dataset without explicit permission from the original authors is strictly prohibited. For commercial use or licensing inquiries, please contact us at puma122707@gmail.com.

Task Categories

  • Time-Series Forecasting

Language

  • English (en)

Tags

  • Finance

Pretty Name

FNSPID: A Comprehensive Financial News Dataset in Time Series

Size Categories

  • 10M<n<100M