Datasets:

KrossKinetic
/

Bloomberg_Financial_News

@@ -1,98 +1,101 @@
----
-license: apache-2.0
-language:
-- en
-tags:
-- finance
-size_categories:
-- 100K<n<1M
----
-# Dataset Card for Processed Financial News Articles (2006-2013)
-This dataset consists of 446762 financial news articles originally sourced from Bloomberg, covering the period from 2006 to 2013. It includes processed texts suitable for use in NLP and financial trend analysis.
-## Dataset Details
-### Dataset Description
-The dataset contains English-language financial news articles collected from Bloomberg. It is designed for natural language processing tasks, financial analysis, and trend detection during the specified period.
-- **Curated by:** Dan Benayoun
-- **Shared by:** Dan Benayoun
-- **Language(s) (NLP):** English
-- **License:** Apache-2.0
-### Dataset Sources
-- **Paper:** https://emnlp2014.org/papers/pdf/EMNLP2014148.pdf
-## Uses
-### Direct Use
-This dataset is intended for academic research, algorithm training, and development of NLP models that require financial context, particularly for sentiment analysis, event detection, and trend tracking over time.
-### Out-of-Scope Use
-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.
-## Dataset Structure
-### Data Instances
-A typical instance includes fields like `Headline`, `Journalists`, `Date`, `Link`, `Article`.
-### Data Splits
-The dataset is not divided into standard training, validation, or test splits.
-## Dataset Creation
-### Curation Rationale
-This dataset was curated to assist researchers and developers in analyzing financial news trends and patterns across several years.
-### Source Data
-#### Data Collection and Processing
-The articles were originally scraped from Bloomberg and processed for easier consumption in NLP tasks.
-#### Who are the source data producers?
-The text of the articles is produced by journalists and financial analysts at Bloomberg.
-### Annotations
-#### Personal and Sensitive Information
-The dataset contains information that could be considered personal or sensitive as it includes names of people, companies, and possibly their financial data.
-## Bias, Risks, and Limitations
-The dataset reflects the potential biases of Bloomberg's reporting style and period-specific geopolitical influences on financial reporting.
-### Recommendations
-Care should be taken to account for these biases when using the dataset for modeling or analysis.
-## Citation
-**BibTeX:**
-```bibtex
-@misc{processed_bloomberg_financial_news_2006_2013,
-  author = {Dan Benayoun},
-  title = {Processed Dataset of Financial News Articles from Bloomberg (2006-2013)},
-  year = {2024},
-  publisher = {HuggingFace},
-}
-@misc{BloombergReutersDataset2015,
-  author = {Philippe Remy, Xiao Ding},
-  title = {Financial News Dataset from Bloomberg and Reuters},
-  year = {2015},
-  publisher = {GitHub},
-  journal = {GitHub repository},
-  howpublished = {\url{https://github.com/philipperemy/financial-news-dataset}}
 }

+---
+license: apache-2.0
+language:
+- en
+tags:
+- finance
+size_categories:
+- 100K<n<1M
+---
+# Json version of the original dataset.
+# Original Dataset : https://huggingface.co/datasets/danidanou/Bloomberg_Financial_News
+# Dataset Card for Processed Financial News Articles (2006-2013)
+This dataset consists of 446762 financial news articles originally sourced from Bloomberg, covering the period from 2006 to 2013. It includes processed texts suitable for use in NLP and financial trend analysis.
+## Dataset Details
+### Dataset Description
+The dataset contains English-language financial news articles collected from Bloomberg. It is designed for natural language processing tasks, financial analysis, and trend detection during the specified period.
+- **Curated by:** Dan Benayoun
+- **Shared by:** Dan Benayoun
+- **Language(s) (NLP):** English
+- **License:** Apache-2.0
+### Dataset Sources
+- **Paper:** https://emnlp2014.org/papers/pdf/EMNLP2014148.pdf
+## Uses
+### Direct Use
+This dataset is intended for academic research, algorithm training, and development of NLP models that require financial context, particularly for sentiment analysis, event detection, and trend tracking over time.
+### Out-of-Scope Use
+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.
+## Dataset Structure
+### Data Instances
+A typical instance includes fields like `Headline`, `Journalists`, `Date`, `Link`, `Article`.
+### Data Splits
+The dataset is not divided into standard training, validation, or test splits.
+## Dataset Creation
+### Curation Rationale
+This dataset was curated to assist researchers and developers in analyzing financial news trends and patterns across several years.
+### Source Data
+#### Data Collection and Processing
+The articles were originally scraped from Bloomberg and processed for easier consumption in NLP tasks.
+#### Who are the source data producers?
+The text of the articles is produced by journalists and financial analysts at Bloomberg.
+### Annotations
+#### Personal and Sensitive Information
+The dataset contains information that could be considered personal or sensitive as it includes names of people, companies, and possibly their financial data.
+## Bias, Risks, and Limitations
+The dataset reflects the potential biases of Bloomberg's reporting style and period-specific geopolitical influences on financial reporting.
+### Recommendations
+Care should be taken to account for these biases when using the dataset for modeling or analysis.
+## Citation
+**BibTeX:**
+```bibtex
+@misc{processed_bloomberg_financial_news_2006_2013,
+  author = {Dan Benayoun},
+  title = {Processed Dataset of Financial News Articles from Bloomberg (2006-2013)},
+  year = {2024},
+  publisher = {HuggingFace},
+}
+@misc{BloombergReutersDataset2015,
+  author = {Philippe Remy, Xiao Ding},
+  title = {Financial News Dataset from Bloomberg and Reuters},
+  year = {2015},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished = {\url{https://github.com/philipperemy/financial-news-dataset}}
 }