AlchemyAPI adds Advanced Sentiment Analysis to Text-Mining Web Service

Leading natural language processing technology provider, AlchemyAPI, has recently added advanced sentiment analysis functionality to its text-mining web service.

A SaaS (News - Alert) platform designed to power a variety of product and data-mining use cases, AlchemyAPI helps various online publishers, news aggregators, and contextual advertising firms world-wide to enhance website, blog, content management system, or semantic web application. The platform helps these organizations to understand and get advance visibility on profit margins for online content.

"Our sentiment engine provides the ability to identify opinions within vast quantities of data," said Elliot Turner (News - Alert), CEO of AlchemyAPI, in a statement.  "Sentiment analysis is critical for organizations wishing to understand consumer trends and customer perceptions, and AlchemyAPI's semantic technology provides best-of-breed capability."

Available as both a free online API and commercial subscription service, AlchemyAPI AlchemyAPI uses statistical natural language processing technology and machine learning algorithms to analyze content, extracting semantic meta-data: information about people, places, companies, topics, languages, and more.

AlchemyAPI undertakes sentiment analysis at Document-level, entity-level, and keyword-level.

"AlchemyAPI has been specifically tuned to understand user-generated, short-form social media content as well as editorialized text," Turner stated.

Sentiment analysis functionality is available immediately to all AlchemyAPI users.

With its solutions, AlchemyAPI helps companies world-wide enhance, understand, and better-leverage their textual information assets. The AlchemyAPI web service provides publishers with the tools and capabilities necessary to compete in today's highly-interconnected global information economy.

Recently, Orchestr8 (News - Alert) upgraded its AlchemyAPI content analysis online service to include expanded language coverage with the addition of Portuguese and Swedish, enhanced text categorization, and integration with Linked Data standards. The new release also provides integrated support for Linked Data standards and RDF (Resource Description Format) semantic Web standards, and integrates content links to online databases such as Wikipedia, GeoNames, and The Central Intelligence Agency (CIA) World Factbook.

Rahul Arora is a TMCnet contributor. He has worked as an editor and freelance writer for several reputed organizations in India. To read more of his articles, please visit his columnist page.

Edited by Jennifer Russell