RavenPack News Analytics

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

搜集汇总

背景与挑战

背景概述

RavenPack News Analytics 是一个提供历史与实时结构化分析的数据集，覆盖超过4万个新闻与社交媒体源，包括高端媒体如Dow Jones和国际媒体。它利用专有NLP技术自动标注超过1200万个实体和7000多个事件主题，提供情感评分、相关性等分析，数据日内更新。