News Analysis Process

RavenPack's news analysis techniques bring cutting-edge linguistic methodologies supported by enterprise-level server infrastructure to any desktop computer with a standard internet connection. Capable of processing hundreds of thousands of stories per day from diverse sources in varied formats, RavenPack's news analysis detects and delivers only actionable trends critical to the user's environment.

The streamlined news analysis process receives, analyzes, archives and delivers analytics in milliseconds. Whether a user is interested in receiving real-time news events, analyzing short term trends or researching a news and text archive, RavenPack's datacenters are designed to deliver analysis previously only available to high-end researchers.

Deploying the latest linguistic analysis techniques, RavenPack offers clients the flexibility of choosing the methodology most suited to their needs. Bayes training, vector classification, word/phrase lists, pattern detection and market response-based analysis are just a few techniques RavenPack deploys in conducting news sentiment analysis. Additionally, the company has developed significant technologies targeted at value extraction, elementization, and other types of structured analysis that underpin the new language of machine-readable news.

Experts at standardizing metadata from diverse news sources, RavenPack gives an unparalleled view of global news information by delivering trends, sentiment, subject and extracted analysis without obligating the client to extensive infrastructure and research expenses.

To learn more about RavenPack's news analysis, email info@ravenpack.com