Text Structuring, Analytics & Sentiment
This page will provide you with access to example use cases to power natural language processing (NLP) workflows using Refinitiv APIs. On the right are a series of articles describing use cases in detail complete with code examples, snippets and samples, as well as full jupyter notebooks and source code available on Github. At the bottom of the page you will find links to related APIs, with Overview, Quick Start Guide, full Documentation and Tutorials
Power text structuring, analytics and sentiment workflows using our powerful set of APIs and Feeds, available via desktop solutions, SDKs and enterprise level APIs where redistribution of content is required. Our web APIs provide a broad range of language support so you have unlimited integration options. These include Python so you can access all wide set of open source libraries that are available.
Structuring unstructured text
Use our APIs to leverage insights and derive meaning in unstructured content including research, email corpus, messaging, Twitter, LinkedIn, Blogs, RSS , News, Governement Filings, Corporate Filings. Use Natural Language Processing, Text Analytics and Data-Mining technologies to tag people, places, facts and events. Assign financial topics and themes to increase content value, accessibility and interoperability.
Use Cases Include:
- Enhance internal research pipelines
- Generating Alpha (mining news, government filings etc)
- Accurately predict & leverage alpha signals
- Uncover links between people, places & more
- Manage Risk by identifying events types
Use our APIs to derive text analytics and insights from news, corporate or government filings, web-scraped data, structured text and unstructured text leveraging natural language processing. discover how news, company overviews, corporate filings, government filings, research reports can help drive decisions in whole new ways. Ingest this content into your text analytics pipeline to power downstream workflows.
Use our APIs to grade how positive or negative and objective or subjective a piece of text is to augment research and strategy
Machine Readable News
Available via our real-time streaming APIs, Machine Readable News (MRN) is an advanced service for automating the consumption and systematic analysis of News. It delivers deep historical news archives, ultra-low latency structured news and news analytics (such as sentiment) directly to applications. This enables algorithms to exploit the power of news to seize opportunities, capitalize on market inefficiencies and manage event risk. Content ranges from binary and economic headline data for event-based trading, sentiment and buzz metrics for quantitative uses, and raw news with metadata for intraday trading and market surveillance. Use MarketPsych Indices to convert the volume of news and social media into manageable market sentiment data to predict market moves.