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We ran a study comparing NewsCatcher news pipelines with alternative methods of gathering news data. Check the results.

Explore strategies for measuring product launch success through swift news insights. Learn how to analyze media impact, track brand visibility, and interpret competitor reactions effectively in our latest article.

NewsCatcher teams up with Reworkd to deliver analysts more reliable, enriched, and comprehensive data that goes beyond just news.

Discover the Top 50 Media Outlets analysts rely on for hyper-local news and insights in 2025. Curated based on reputation, speed, depth, diversity, and frequency, this guide empowers professionals to navigate the ever-changing media landscape with confidence.

The Local News API provides city-specific news for over 31,000 U.S. locations, solving issues like keyword mix-ups and article relevance. Learn how it works and why it’s built this way.

Discover how Transparency International uses the NewsCatcher API to uncover corruption cases from thousands of news articles.

NewsCatcher’s Hyperlocal News API delivers precise, city-focused news by scanning thousands of articles daily across 31,000 U.S. locations—perfect for planners, businesses, and developers seeking local insights.

By leveraging sentiment analysis, market researchers can better understand public perception, forecast trends, and stay ahead of competitors, driving more strategic and responsive business decisions.

The success of news analysis relies on selecting a vendor that provides both vast volumes of news data and AI-powered enrichment, enabling businesses and researchers to extract meaningful insights.

Pangram Labs found 6.96% of 857,434 news articles from July 1, 2024, were AI-generated, underscoring the need for better detection to prevent fraud and disinformation.

Understand the need for news syndication and the various ways you can aggregate news data yourself. Learn to build your own crypto news aggregator.

What is text classification? How does do text classifiers work? How can you train your own news classification models?

What is natural language processing? How does it work? Where is NLP used in the real world?

Four easy-to-use open-sourced Python web scraping libraries to help you build your own news mining solution.

Learn how to use sentiment analysis to mine insights about from tweets and news articles

We'll go in-depth on what, why, and how of text normalization. With code examples written in SpaCy and NLTK Python libraries.

Annotation is the part where most projects stall, and it can make or break your models. Here are some tools and tips to help you with text annotation needs.

Learn to write an information extraction NLP pipeline using spaCy’s Matcher. It will extract dividend information from news headlines and articles.

You can get a pretty narrowed Google News RSS feed of aggregated news: search by keyword, geo position, time range, topic, etc. You just need to know the syntax. Unfortunately, Google does not provide any official documentation, so we'll try to fill the gap.

How To Annotate Entities With Spacy PhraseMatcher

From today, you can use our NewsCatcher API service for free when you search for the news that talks about COVID-19.

A practical guide to releasing and presenting open-sourced projects to be mentioned by other people

We are a team of 2 data engineers. From February to March 2020 we dedicated most of our spare time building an API that allows you to search for the news articles’ data.

Cost optimization replacing Cloud Run with Kubernetes Pods

Media monitoring is the right way to never miss a story about your brand, your competitors, and your industry.

By the end of this tutorial, you will be able to write a Named Entity Recognition pipeline using SpaCy: it will detect company acquisitions from news headlines.

The ultimate guide to where to search for online published news articles. open-sourced & free tools only. Use it to build a News API alternative.

Learn what is named entity recognition, how it works, and how it can be used. Use spaCy to train your own custom NER model.

All `topics` have 15k articles except for SCIENCE which is 3774. Those articles are published by thousands of different news websites.

Were running our News API startup for over a year. We share our biggest takeaways.

Learn the different similarity measures and text embedding techniques. Play around with code examples and develop a general intuition.