Show HN: NewsCatcher's Hyperlocal News API – Granular City-Level News Feeds
Why We Built It:
Aggregating hyperlocal news is complex. Local news comes from diverse sources, many covering national topics, making it hard to isolate local events like transit updates, crime, extreme weather alerts, or infrastructure projects. Searching by location alone can lead to irrelevant results, especially with city names that overlap or match common words (e.g., Orange, Lake).
What It Does:
Our API provides precise, location-based news by processing 185K articles daily and tagging each with its associated_town down to the town level with 92% accuracy. Covering 31,000 U.S. locations, it uses advanced NLP to accurately associate location names, even when they’re common words.
It enables you to:
- Access near-real-time, location-focused news feeds
- Filter by topic (e.g., crime, sports), keyword, and date
- Cluster articles covering similar events and topics
- Get sentiment score for a headline and article body
- Recognize and extract entities
Key Features:
- AI-powered location recognition and validation
- Advanced querying with boolean operators and proximity search
- Multiple town association methods for precise location matching
- NLP-enriched content for deeper analysis
- Articles clustering
- Multi-language support
- High volume data retrieval (up to 1000 articles per request)
For a demo, try our 15 public RSS feeds: https://www.newscatcherapi.com/local-news/rss/. The API provides JSON output for easy integration.
Tech Specs:
- RESTful, JSON-based API
- API key authentication
- Scalable for high-volume queries
We’d appreciate any feedback or questions on use cases.