AlchemyAPI is excited to sponsor the fourth Sentiment Analysis Symposium held on May 8, 2012 in New York. Text analytics industry analyst Seth Grimes announced an agenda featuring a wide variety of sessions from, “How the Media Uses Sentiment Analysis: A Perspective from the Wall Street Journal” to “Tween Pants Cut Too Low!! (or, Combine Survey Research & Social Monitoring to Discover the Unknown).”

“AlchemyAPI performs sentiment analysis on tens of millions of pieces of content daily for customers in a variety of market verticals such as news distribution, media monitoring, and public relations,” said founder and CEO Elliot Turner. “We’re happy to sponsor the sentiment analysis symposium and help promote the power of text analytics to unlock valuable insights in big data.”

Are you attending? Leave a comment and let us know.

What is this thing?
It’s a demo for our author extraction service. An explanation of a service can only go so far, so we created a simple app to make it easier to see what author extraction is all about.

Why do I care?
AlchemyAPI is the first text mining platform able to extract an author from a blog or news post.  This author extraction API can be used in any application where you need to sort through thousands of online news or blog posts by author.

Can you give me an example of a particular author you extracted?
TechCrunch was one of 11 news publications we scanned with AlchemyAPI. MG Siegler was one of the 30 authors we extracted from 2304 TechCrunch articles. His bio states that he focuses on Apple and our results support this claim, since the top five keywords found from 69 of his articles are all Apple-related. Here is the breakdown of his detected keywords by article count:  App Store (11), iPhone 4 (8), new iPad (8), Steve Jobs (7), and battery life (5). The top company is Apple (33), the top person is Steve Jobs (9), and top location is U.S. (10).

I’m an author, am I identified in this demo?
If you write for any of the following publications, it’s likely you are one of the 316 authors identified: Forbes, TechCrunch, GigaOM, ReadWriteWeb, Wall Street Journal, AllthingsD, Washington Post, ZDNet, Fast Company, ProgrammableWeb.

Can you show me how to use this demo app?
Yes, here is a screencast.

This morning, Adam DuVander at ProgrammableWeb announced our release of the first text mining service able to extract the author from an online document: “API Billionaire Adds Author Extraction Service.” Simply put, author extraction makes it possible to automatically find the author of a blog post or news article.

Author Extraction Benefits Social Media Monitoring Companies

Anyone using a top-tier social media engagement platform knows the power they provide, making it possible to analyze large amounts of data in a short amount of time. One drawback, however, is that influencer results are organized by media publication, not by writer (except for Twitter, which treats each user as an author).

For example, say you are in the field of Big Data and TechCrunch is a major influencer writing about that topic, wouldn’t you rather have a list of which TechCrunch writers are writing about Big Data? Most likely you would. If you add sentiment analysis to the mix, the possibilities open up even further, giving you the power to see which TechCrunch blogger writes the most positively about Big Data.

You might be wondering why companies can’t just identify an author manually. Well, they can and have been. Just like you and I can manually count all of the words in this blog post. For example, MediaConnect, creator of the media engagement platform Influencing, had been identifying authors by hand before using author extraction. But according to Moreover Technologies, an aggregator of social media, there over 2 million blog posts being published every day, or 20 blog posts per second. This makes it impossible for a company to manually sift through all of them. By contrast, AlchemyAPI processes over 80 million documents per day, or 1000 per second. Now that MediaConnect uses AlchemyAPI’s author extraction, they spend their extra time focusing on expansion.

Author Extraction Also Benefits PR Firms

During the Age of Big Data, PR firms that master data analysis stay competitive. One such company is Waggener Edstrom, one of the largest global independent communications firms in the world. They use AlchemyAPI’s author extraction in their own “intelligent applications,” helping their clients and staff better understand online influence. According to David Kohn, Vice President of Software Development, “The addition of author extraction improves our products and lowers the cost of manual data collection.”

Author extraction is now available to all AlchemyAPI users and customers. For more information, go to: www.alchemyapi.com/authorextraction

Today marks the release of exciting new AlchemyAPI functionality: Relation Extraction & Directional-Sentiment Analysis.

Relation extraction identifies facts, events, buying signals, targeted customer sentiment, and more inside raw text:

Designed to power a new breed of customer opinion tracking, automated lead generation, document analysis and data visualization applications, AlchemyAPI’s relation extraction API processes natural language, converting documents and web pages into actionable, semantically enriched “Subject-Action-Object” data.

AlchemyAPI also now offers directional-sentiment analysis. This means understanding the source of an opinion and who or what it is directed towards.  Here’s an example of directional-sentiment in action:

“Ugly Bob attacked beautiful Susan.”

AlchemyAPI decodes three different sentiment values for the statement above.  It marks “Bob” as negative (because he was indicated as being “Ugly”), and Susan as positive (because she is “beautiful”).  Additionally, using directional-sentiment, AlchemyAPI decodes the fact that Bob is emitting negative sentiment towards Susan (he is attacking her).  Named entity extraction is also incorporated, so AlchemyAPI knows that Bob and Susan are both Persons.

Directional-sentiment and relation extraction expands AlchemyAPI’s significant arsenal of text-analysis capabilities, and we look forward to seeing the innovative tools and applications built by our customers and user community using these new features.

In other news: AlchemyAPI processed more than 2 billion customer API transactions last month.  For those counting, this is over 700 text analysis operations every second performed by our platform.  We’re excited about this continued growth and proud to see AlchemyAPI leveraged by customers in 5 continents and more than one dozen countries.

Today we’re announcing a significant new update to AlchemyAPI.

Over the past 2 years, our platform has earned a reputation as one of the fastest natural language processing solutions available anywhere.  This release further advances the state-of-the-art, offering nearly 100% faster text analysis performance while simultaneously increasing linguistic accuracy.

Built to power a growing number of time-sensitive business applications, such as real-time stock trading and information routing, AlchemyAPI’s latest update further advances its performance lead over competing platforms, providing the ability to analyze hundreds of documents per second with extremely low latency.

Natural language processing functionality has also been significantly expanded, with the addition of new co-reference resolution capability and improved entity disambiguation functionality.

Co-reference functionality provide the ability to resolve “referent” mentions within a document back to their source entity.  AlchemyAPI’s capability goes beyond the simple “he / she” heuristics found in competing systems to provide true, linguistically driven mention resolution:

Example #1:

Example #2:

Our disambiguation engine has also seen a significant update in this release, providing increased accuracy and faster performance.  For more information on AlchemyAPI’s named entity disambiguation functionality, click here.

Performance and feature updates are available immediately to all AlchemyAPI users.

AlchemyAPI will also be exhibiting later this week at the 2011 GLUE conference.  If you’re attending, stop by booth #7 to see what’s in store for our next release!

Today we officially announced the release of new sentiment analysis functionality within AlchemyAPI.  We have been quietly testing this new capability with a number of partners for the past few months, and are happy to make it available today to the broader AlchemyAPI community.

AlchemyAPI’s sentiment API provides a variety of features, including document-level, entity-targeted and keyword-targeted sentiment mining.  We’re also supporting negation handling, sentiment amplifiers / diminishers, slang, and typos.  AlchemyAPI’s sentiment engine is also fully trainable, providing easy integration into niche applications or for handling specific content types.

More information on AlchemyAPI’s new sentiment engine is available here.

In other news, AlchemyAPI will be exhibiting March 23rd at the Structure Big Data 2011 conference in NYC.  If you’re attending, stop by our booth!

We’re been super busy over the past few months rolling out new AlchemyAPI updates, SDKs, and 3rd-party integrations.  Response from our new Concept Tagging API has been fantastic; we’re seeing great uptake for this feature and all sorts of new customer applications built around it.

Our customers and partners know we’ve been testing new Sentiment Analysis functionality as well, something we’re truly excited about deploying to our general user population.  Named entity disambiguation and sub-type resolution has been greatly expanded, decoding hundreds of new entity sub-types (ranging from Athletes to Comic Book Artists!)

The last few months have seen a wide variety of integrations into 3rd party tools & applications:  Drupal plugins, WordPress extensions, Web Browser Extensions, Data Visualization Tools, Yahoo Pipes modules, Unix/Linux command-line NLP tools, and more.  One of our team’s favorites is the BBC’s experimental interactive TV system, which leverages AlchemyAPI to analyze closed captioning data in real-time, showing WWW content recommendations on your TV that are related to what’s being talked about.  Have you seen or created any exciting AlchemyAPI integrations?  Please tell us!  We love to hear about them.

Our team at Orchestr8 has really enjoyed making premier NLP technology available to our partners and customers via AlchemyAPI, and we’re only getting started.  Orchestr8 is growing rapidly, currently hiring more engineers & NLP geeks, and preparing to release some really exciting new technology in the realm of Big-Data Analytics (with a NLP twist!).

Today we’re announcing a new AlchemyAPI release, containing significant enhancements to our Keyword Extraction API.

A new “GetRankedKeywords” API is now available, exposing relevance scores for extracted keywords.  These scores represent the overall importance of a given keyword to a document.

AlchemyAPI’s Keyword Extraction API also contains a number of under-the-hood enhancements, which result in even better & more relevant keywords for your content.

We’ve released updates to the AlchemyAPI SDKs as well, exposing our new Keyword API for quick integration into your application.

Stay tuned for more updates & AlchemyAPI enhancements.

PS. — Do you love NLP, text analytics, and the semantic web as much as we do?  Join our team!  AlchemyAPI is now hiring for a number of positions, including linguistic annotators, QA engineers, and core NLP developers.

To keep up with our growth for 2010, AlchemyAPI is moving into new offices!  We’re now located in the heart of Denver, in the Riverpoint Building @ Confluence Park.

2010 is turning out to be a great year for AlchemyAPI.  We’ve seen integration into a wide variety of third-party applications & services, including Apache UIMA, Wandora, Google Wave, and JackBe’s Presto Cloud platform.  AlchemyAPI has seen thousands of new users and massive growth in daily API calls served.  Recently, our product team has been previewing exciting new functionality to select customers and partners, and we will be rolling these capabilities out to our entire user community very soon.

Keep reading for more updates!

Today we’re announcing both a new AlchemyAPI service update, and a totally revamped AlchemyAPI.com website design.

The AlchemyAPI service update contains several notable enhancements:

• URL Link Un-Shortening - Links are automatically un-shortened for any URL content submitted for one of the 80+ URL Link Shorteners currently in existence (bit.ly, tinyurl, etc).  API responses now include un-shortened URL information.

• CrunchBase Integration - Named entity API responses now include linkages to CrunchBase entries for thousands of technology and startup companies.  Semantic CrunchBase support has also been included.

• Named Entity Disambiguation Updates - Increased coverage (30%+ increase in disambiguation coverage) and increased precision (more accurate entity disambiguations)

Here’s a peek at the new AlchemyAPI.com (kudos to our designer, Archie, for doing a great job!):

Some truly exciting things are in the pipeline for AlchemyAPI in Q4 of 2009; keep watching for the next update!