NEWS ARTICLES DATASET

Clean news data,
entities and sentiment.

// THE SHORT ANSWER

News-articles datasets are ready-to-license structured news data — clean article text, headlines, publication dates, sources, extracted entities and sentiment scores — from news outlets. iWeb Data Scraping delivers them de-duplicated and enriched, so NLP teams, researchers and investors can work with news data without building collection, cleaning and entity/sentiment enrichment themselves.

Get free sample in 48h See the data
99%+field accuracy, QA-verified
48hfree sample turnaround
24/7pipeline monitoring
ISO 27001+ 9001 certified

Key facts

  • Data point: Headline
  • Data point: Clean article text
  • Data point: Publication date
  • Data point: Source

News is a firehose that's messy to consume programmatically — boilerplate, duplicates, paywalls, inconsistent formats. Our news datasets deliver it clean: article text, headlines, entities and sentiment, deduplicated and structured for NLP and analysis.

License a snapshot or subscribe for a real-time feed. For continuous, filtered news pipelines, see news & media feeds.

THE POINT

One vertical, every platform that matters in it — matched into a single feed your team actually uses.

DATA POINTS WE EXTRACT

What's in the dataset.

Headline
Clean article text
Publication date
Source
Extracted entities
Sentiment score
Category / topic
Author (if public)
URL
Language
Location mentions
Timestamp
SEE THE DATA FIRST

What you'll actually receive.

Real sample structure from this feed. Your free 48-hour sample comes in your category, in this shape — CSV, JSON or straight to your warehouse.

News dataset — clean article text, entities, sentiment.
published_at source headline_snippet entities sentiment
2026-07-08 Reuters Retailer posts record quarter as... ExampleCo; India +0.5
2026-07-08 Bloomberg Sector faces margin squeeze amid... Retail -0.3
2026-07-07 ET Startup raises Series B for... StartupX +0.6
2026-07-07 Mint Regulator proposes new rules on... Policy -0.1
↑ Sample structure — illustrative values. Your data reflects your platforms and category. Get this for your data →
WHO USES THIS

Built for the person
who owns the number.

NLP / AI TEAM

Train and test models

Clean, entity-tagged news text for NLP models and pipelines.

INVESTOR / ALT-DATA

Track sentiment

Entity-linked news sentiment on companies and sectors over time.

RESEARCHER / MEDIA

Study coverage

Structured news data to analyze topics, sources and framing.

RELATED:News & Media Feeds →Alternative Data →AI & LLM Training Data →
FAQ

Before the first call.

Headlines, clean article text (boilerplate removed), publication dates, sources, extracted entities, sentiment scores, category/topic, public author, URL, language, location mentions and timestamps — deduplicated and enriched.

Yes — boilerplate, navigation and ads are stripped, leaving clean article text, and near-duplicates (syndication, mirrors) are removed. Entities and sentiment are added, so the data is analysis-ready rather than raw HTML.

Entity-linked news sentiment on specific companies and sectors, tracked over time, is a signal investors combine with other alt-data. We map mentions to entities and score sentiment so the trend is measurable.

We provide structured metadata, entities, sentiment and excerpts for analysis rather than republishing full copyrighted articles. Licensing terms are set to your use case (NLP training, internal analysis) and agreed up front.

Get a free sample dataset in 48 hours.