Dan Benayoun
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license: apache-2.0
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---
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license: apache-2.0
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language:
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- en
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tags:
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- finance
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size_categories:
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- 10K<n<100K
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---
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# Dataset Card for Processed Financial News Articles from Reuters (2006-2013)
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This dataset consists of 105,359 financial news articles originally sourced from Reuters, covering the period from 2006 to 2013. It includes processed texts with an additional 'Summary' field, suitable for use in NLP and financial trend analysis.
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## Dataset Details
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### Dataset Description
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The dataset contains English-language financial news articles collected from Reuters. It is designed for natural language processing tasks, financial analysis, and trend detection during the specified period.
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- **Curated by:** Dan Benayoun
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- **Shared by:** Dan Benayoun
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- **Language(s) (NLP):** English
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- **License:** Apache-2.0
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### Dataset Sources
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- **Paper:** [Financial News Dataset Analysis](https://emnlp2014.org/papers/pdf/EMNLP2014148.pdf) - This paper discusses methodologies for processing financial news datasets.
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## Uses
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### Direct Use
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This dataset is intended for academic research, algorithm training, and development of NLP models that require financial context, particularly for tasks such as sentiment analysis, event detection, and trend tracking over time.
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### Out-of-Scope Use
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The dataset should not be used for real-time financial decision-making or trading due to its historical nature and the inherent biases of media reporting.
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## Dataset Structure
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### Data Instances
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A typical instance includes fields like `Headline`, `Journalists`, `Date`, `Link`, `Article`, and `Summary`.
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### Data Splits
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The dataset is not divided into standard training, validation, or test splits.
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## Dataset Creation
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### Curation Rationale
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This dataset was curated to assist researchers and developers in analyzing financial news trends and patterns across several years, with the addition of summaries to aid in quicker understanding and analysis.
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### Source Data
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#### Data Collection and Processing
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The articles were originally scraped from Reuters and processed for easier consumption in NLP tasks, including the generation of summaries for each article.
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#### Who are the source data producers?
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The text of the articles is produced by journalists and financial analysts at Reuters.
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## Annotations
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### Personal and Sensitive Information
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The dataset contains information that could be considered personal or sensitive as it includes names of people, companies, and possibly their financial data.
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## Bias, Risks, and Limitations
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The dataset reflects the potential biases of Reuters' reporting style and period-specific geopolitical influences on financial reporting.
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### Recommendations
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Care should be taken to account for these biases when using the dataset for modeling or analysis. Researchers should also consider the implications of using summary data which may omit critical information or context.
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## Citation
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**BibTeX:**
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```bibtex
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@misc{reuters_financial_news_2006_2013,
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author = {Dan Benayoun},
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title = {Processed Dataset of Financial News Articles from Reuters (2006-2013)},
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year = {Year of dataset release},
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publisher = {Dataset publisher},
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}
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@misc{BloombergReutersDataset2015,
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author = {Philippe Remy, Xiao Ding},
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title = {Financial News Dataset from Bloomberg and Reuters},
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year = {2015},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/philipperemy/financial-news-dataset}},
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}
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