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Breaking news represents important stories rapidly gaining traction across multiple sources. News API identifies these events by analyzing coverage patterns and grouping articles by content similarity — surfacing high-impact events as they emerge.

How it works

1

Clustering

Recently published articles are automatically grouped based on content similarity.
2

Validation

Each cluster is analyzed for breaking news signals: sudden spikes in publication frequency, coverage across multiple publishers, and presence of high-ranking news sources.
3

Deduplication

Duplicate content within clusters is filtered out while preserving source diversity.
4

Historical analysis

New candidates are compared against recent breaking news to track continuing stories.
5

AI evaluation

An AI analysis step confirms whether a cluster represents a significant event.
6

Classification

Clusters meeting the breaking news criteria receive a special flag in the system.
When you query /breaking_news, you receive the most representative article from each breaking news cluster. Results are ordered by cluster size, so the most widely covered stories appear first.

Query endpoint

Response format

For a full description of response fields, see the Breaking news endpoint reference.

Comparison with other endpoints

Use cases

  • Media monitoring — quickly identify emerging stories without tracking multiple sources manually.
  • Content curation — surface trending stories for newsletters, apps, or websites based on coverage traction.
  • Market intelligence — detect potentially market-moving events as they gain media coverage.
  • Crisis monitoring — identify sudden surges in coverage about topics of concern.

See also