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# FNSPID: A Comprehensive Financial News Dataset in Time Series |
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## Description |
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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. |
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[Link to Github Program](https://github.com/Zdong104/FNSPID_Financial_News_Dataset) |
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## Key Features |
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- **Extensive Coverage:** The dataset contains over 10 million entries, offering broad insights into the financial news landscape. |
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- **Time-Series Analysis Ready:** Organized in a time-series format, FNSPID is ideal for forecasting financial market movements and trends. |
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- **Diverse Applications:** Suitable for various tasks including sentiment analysis, market prediction, and trend analysis. |
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## Citation |
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If you use the FNSPID dataset in your research, please cite our work as follows: |
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```bibtex |
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@misc{dong2024fnspid, |
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title={FNSPID: A Comprehensive Financial News Dataset in Time Series}, |
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author={Zihan Dong and Xinyu Fan and Zhiyuan Peng}, |
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year={2024}, |
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eprint={2402.06698}, |
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archivePrefix={arXiv}, |
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primaryClass={q-fin.ST} |
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} |
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``` |
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## License |
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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. |
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## Prohibition of Commercial Use |
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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`. |
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## Task Categories |
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- Time-Series Forecasting |
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## Language |
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- English (en) |
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## Tags |
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- Finance |
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## Pretty Name |
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FNSPID: A Comprehensive Financial News Dataset in Time Series |
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## Size Categories |
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- 10M<n<100M |
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--- |