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README.md

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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](https://github.com/Zdong104/FNSPID_Financial_News_Dataset)
+
+## 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:
+
+```bibtex
+@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
+
+---

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