CNN news data

Description

Explore a comprehensive archive of over 444,000 historical CNN news articles sourced directly from cnn.com. This rich dataset provides essential fields including full article content, title, link, author, publication date, category, and keywords, offering a deep look into CNN's extensive reporting. Perfect for researchers, journalists, and data scientists seeking robust news content for media analysis, trend detection, or training AI models.

Highlights

  • Over 444,000 CNN news articles.

  • Extensive CNN.com news content archive.

  • News articles with detailed publication dates.

  • Rich details: content, images, author, keywords.

Sample Data

Preview of available data:

Link Title Author Content Country Version Category Keywords Language Publisher Site Name Scraped At Word Count Description Imported At Header Image Published At
https://www.cnn.com/2010/03... What’s in a name? \N \N \N 1775528129459 tv \N en CNN cnn.com 2026-04-06T10:48:57Z 0 [cnn-video url=”http://www.... 2026-04-07 02:15:29 \N 2010-03-10T15:56:52Z
https://www.cnn.com/2010/03... Friday March 19 \N Go to CNN.com or CNN.com/Li... \N 1775528129459 tv \N en CNN cnn.com 2026-04-06T19:17:06Z 56 Go to CNN.com or CNN.com/Li... 2026-04-07 02:15:29 \N 2010-03-16T14:54:48Z
https://www.cnn.com/2010/03... Friday March 19 \N Go to CNN.com or CNN.com/Li... \N 1775528129459 tv \N en CNN cnn.com 2026-04-06T14:07:47Z 56 Go to CNN.com or CNN.com/Li... 2026-04-07 02:15:29 \N 2010-03-16T14:54:48Z
https://www.cnn.com/2010/03... Watch ‘John King, USA (BETA... \N Friday at 12 noon ET head ... \N 1775528129459 tv \N en CNN cnn.com 2026-04-01T03:39:31Z 135 Friday at 12 noon ET head t... 2026-04-07 02:15:29 https://media.cnn.com/api/v... 2010-03-19T00:08:00Z
https://www.cnn.com/2010/03... Watch ‘John King, USA (BE... \N Friday at 12 noon ET head ... \N 1775528129459 tv \N en CNN cnn.com 2026-03-31T21:17:12Z 135 Friday at 12 noon ET head t... 2026-04-07 02:15:29 https://media.cnn.com/api/v... 2010-03-19T00:08:00Z
https://www.cnn.com/2010/03... Make your case, America! \N On Friday, CNN.com or CNN.c... \N 1775528129459 tv \N en CNN cnn.com 2026-04-01T03:37:52Z 161 On Friday, CNN.com or CNN.c... 2026-04-07 02:15:29 \N 2010-03-18T22:27:12Z
https://www.cnn.com/2010/03... After the show \N After the first show, John ... \N 1775528129459 tv \N en CNN cnn.com 2026-03-31T22:19:48Z 38 After the first show, John ... 2026-04-07 02:15:29 \N 2010-03-20T02:51:37Z
https://www.cnn.com/2010/03... High speed Internet for all \N \N \N 1775528129459 tv \N en CNN cnn.com 2026-04-01T03:40:48Z 0 [cnn-video url=”http://www.... 2026-04-07 02:15:29 \N 2010-03-20T02:43:58Z
Sign In to Download

Data Fields

This dataset includes the following data points:

Title
Link
Published At
Author
Publisher
Description
Header Image
Category
Keywords
Country
Content
Word Count
Site Name
Scraped At
Language
Version
Imported At

Why This Data

This news dataset from Cnn provides comprehensive market intelligence and competitive insights. Perfect for:

  • Market Research: Understand market trends and customer preferences
  • Competitive Analysis: Compare pricing, products, and strategies
  • Business Intelligence: Make data-driven decisions
  • Price Monitoring: Track price changes and optimize your pricing

Use Cases

This dataset is perfect for various applications:

Dynamic Pricing & Inventory Management: E-commerce businesses can analyze CNN news content for mentions of supply chain disruptions, economic forecasts, or shifts in consumer behavior (e.g., interest in specific product categories) to inform dynamic pricing adjustments and optimize inventory levels.

Industry & Competitor Monitoring: Market research firms can track CNN's comprehensive coverage to identify emerging industry trends, monitor competitor activities and public perception, and assess the impact of geopolitical or economic events on specific markets.

NLP Model Training & Sentiment Analysis: Data scientists can use the vast text content from CNN articles (titles, descriptions, content) to train and refine NLP models for tasks like sentiment analysis, topic modeling, named entity recognition, and automated news categorization.

Innovation & Trend Forecasting: Product development teams can analyze CNN's reporting on technology, consumer behavior, and societal shifts to identify emerging trends, unmet market needs, and potential areas for product innovation or feature enhancements.

Content Strategy & Keyword Research: SEO specialists and content marketers can analyze CNN's extensive content to identify trending topics, relevant keywords, and high-performing content structures, informing their editorial calendar and optimizing their own content for search visibility.

Get Access to This Dataset

Start using this dataset today. Available in CSV, JSON, and Excel formats with flexible access options.

Request Access Contact Sales

Frequently Asked Questions

This dataset comprises over 444,000 CNN news records, with included samples dating back to 2010. While specific update frequency isn't provided, the 'scraped_at' field indicates the collection date for each article.

The CNN news data is available in a structured format, offering all listed data points like title, content, and publication date. Access methods typically involve API endpoints or bulk file exports, depending on the data provider's setup.

Yes, you can customize the fields received from the comprehensive list of available data points, such as content, author, and category. The dataset also supports filtering by content keywords and specific publication dates to narrow down your results.

This CNN news dataset is valuable for researchers, data scientists, and media analysts for tasks like trend analysis, natural language processing, and historical media research. It enables deep dives into journalistic patterns and public discourse over time.

Yes, sample data records showcasing fields like title, link, and publication date are provided to facilitate understanding of the dataset's structure. For further inquiries or technical assistance, dedicated support channels are typically available to users.