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US Economic News Articles for NLP
Entertainment & Media Consumption
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About
This dataset consists of approximately 8,000 news articles focused on the US Economy. Each article has been tagged for its relevance to the US Economy and analysed for its tone. This dataset is particularly useful for Natural Language Processing (NLP) tasks, offering a valuable resource for sentiment analysis, text classification, and information extraction related to economic news.
Columns
_unit_id: A unique identifier for each unit or article._golden: Indicates whether the entry is a golden record._unit_state: The state of the unit._trusted_judgments: A factor indicating the trustworthiness of the judgments made on the data._last_judgment_at: The timestamp of the last judgment on the article.positivity: A score indicating the positivity of the article's tone.positivity:confidence: The confidence level associated with the positivity score.relevance: Indicates whether the article is relevant to the US Economy (e.g., 'yes' or 'no').relevance:confidence: The confidence level associated with the relevance tag.articleid: A unique identifier for the news article.
Distribution
The dataset typically comes in a CSV format. It contains approximately 8,000 news articles, with the data spanning from 17th November 2015 to 6th December 2015. Specific numbers for rows or records are available, with 8,000 entries represented in total.
Usage
This dataset is ideal for various applications, including:
- Natural Language Processing (NLP) research and model training.
- Developing sentiment analysis models for economic news.
- Creating tools for economic news classification (relevant/not relevant).
- Analysing trends in economic media coverage and public sentiment.
- Training machine learning models for text mining in finance and economics.
Coverage
The dataset's focus is on US economic news articles. The articles cover a time range from 17th November 2015 to 6th December 2015. While the content is specific to the US Economy, the dataset itself is listed with a global region for distribution, meaning it can be accessed worldwide. There are no specific notes on demographic scope within the articles themselves.
License
CCO
Who Can Use It
- Data Scientists and AI/ML Researchers: For developing and testing NLP models on real-world economic text.
- Economists and Financial Analysts: To gain insights into how economic events are portrayed in the media and their perceived relevance.
- Academics and Students: For research projects on economic news sentiment, text analysis, and media studies.
- Media Monitoring Professionals: To track and analyse the coverage of economic topics.
Dataset Name Suggestions
- US Economic News Relevance and Tone Dataset
- US Economic News Articles for NLP
- Economic News Sentiment Analysis Dataset (US)
- US Economy News Articles (2015)
Attributes
Original Data Source:US Economic News Articles (Useful for NLP)
QUALITY