Since 2003, RavenPack has pioneered investment-grade sentiment analysis in financial services. We do not believe in “one size fits all” and have developed multiple sentiment techniques where some leverage millions of rule sets while others use sophisticated machine learning algorithms.
This dataset delivers full historical and real-time structured analytics from premium news sources including:
- Dow Jones
- Wall Street Journal
- Barrons
- MT Newswires
- Benzinga
Analytics are also derived from local, regional, and international newspapers (both in real time, and historically) including Xinhua, El País, La Repubblica, Time Magazine, Washington Post, CNN, reputable blogs and content aggregator sites from more than 40,000 news and social media sources.
Using proprietary Natural Language Processing (NLP) technology, every news story is automatically tagged with topic tags including entities and event categories. RavenPack can recognize over 12 million named entities including companies across all industries, both public and private sectors, individuals, executives, insiders and influencers, geographic locations, products, and services.
Our world-class, finance-oriented taxonomy covers more than 7,000 different event topics and a reference map of securities symbols.
Unique in the marketplace, both our analytics and knowledge graph are point-in-time aware.
For every entity and event detected in a story, RavenPack provides analytics including:
- Sentiment scores
- Relevance metrics
- Novelty tracking
- Temporal scoring
- Topic tagging
Data Update Frequency: Intraday.
For more information, please visit https://www.ravenpack.com/products/edge/data/news-analytics