Dataset
RavenPack News Analytics
Organized intelligence drawn from news outlets and social platforms exceeding forty thousand in number, including tone and sentiment analysis.
Dataset card
ReviewedRavenPack News Analytics converts news and social-media material into structured measures such as sentiment, relevance, novelty and topic tags. This record links to a Snowflake Marketplace listing; the RavenPack product page describes the wider offering and invites prospective users to request a trial.
What this dataset contains
The provider describes insights drawn from more than 40,000 news and social-media sources, with sentiment analysis, relevance scoring, novelty tracking, temporal scoring and topic tagging. That is a provider-reported scope for the product family, not a verified count of sources included in every licensed Snowflake share. Analytics and premium-content rights should be distinguished from unrestricted access to the underlying articles.
Structure and fields
The public product page identifies analytical measures but does not publish a complete schema for this marketplace listing. Confirm entity identifiers, score scales, publication and processing timestamps, document identifiers, deduplication rules and historical coverage from the listing documentation and data dictionary. Marketplace availability or a trial invitation does not establish that a production subscription, redistribution or full-text access is free.
How analysts use it
Researchers can test whether entity-linked news measures add information to event studies, risk monitoring or trading models. Preserve the first available timestamp and distinguish new information from republication, updated stories and later model revisions. Evaluate false entity matches, source changes and out-of-sample results after costs; a sentiment score is not itself a forecast of returns. Vendor claims about adoption or performance are not independent evidence of predictive value.
Discussion
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