Semantic search engine Evri can now understand how the web feels with the launch of their new sentiment web API. While busy scouring the net for people, places, and things and determining the relationships between them, the search engine is now able to understand the feelings associated with these entities, too, be them positive or negative. Using the API, developers can build applications for things like market intelligence, market research, sports and entertainment, brand management, product reviews and more.
At first we thought Evri's API would simply rank things as positive or negative, much like the Twitter tracker twendz does today, highlighting positive, negative, and neutral items. However, the sentiment API does so much more, allowing you deeper insight into the "who's," and "what's," and "why's" associated with the particular expression or feeling.
To be more specific, according to the announcement, Evri lets you:
When unleashed upon the web as a whole, this could unearth a veritable goldmine of information. Just thinking of how many different ways it could be used is enough to blow anyone's mind. Of course, marketers will be the first to jump on board, looking for practical ways to track the feelings about their companies, clients, and brands and why they're changing, but an engine that understands sentiment could do so much more than just this. It can literally take the pulse of the web the way we take the pulse of Twitter using apps like the above-mentioned twendz to rank trends as positive or negative.
To demonstrate what Evri can do, the company created a widget called the "Vibology Meter." (Sadly, no link is provided). The widget not only ranks the good or bad "vibes" about a particular entity (in the example, Barack Obama), but also explores topics associated with that entity and whether or not the primary entity feels positively or negatively towards them. For example, the widget shows Obama is negative towards the GOP and Rush Limbaugh but feels positive about Michele Obama. (Well, that's good!)

When you click on any one of the associated topics (or click on "anything" to see all topics of either positive or negative slant), you're then presented with a sidebar of information. Here, snippets from articles found on the web display along with a title, link, and timestamp.

Of course, this is just a simple example of the Evri API in action. We're sure the developers out there can think up even better ideas than this.
The challenge now for Evri is to keep expanding its index in order to track more sources to rank. At the moment, the engine doesn't track a large slice of the web the way a typical search engine like Google does - in fact they don't even claim to be a search engine...despite what that "Go to" box on their homepage would have you believe. Instead, Evri looks specifically at the people, places, and things on the web and maps the connections between them.
To determine these connections - and now, the associated sentiments as well - Evri pulls from a limited number of "highly regarded" sources. That means you'll definitely see a site like CNN used to rank a person like Obama, but the myriad of tiny politico blogs will be ignored. That's actually a shame, since delving into this "long tail" of the web could give a better overall picture of how all people really feel, not just the sentiments expressed on high-profile sites written by top bloggers and journalists. Still, we know indexing and parsing this long tail is something that's much easier said than done.
In the end, what Evri's doing, even on this smaller scale, is definitely interesting. We hope to see the new API put to good use in the near future.
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This is awesome! Hello Web 3.0??
I've heard the HuPo is using such technology to ease moderation on their website, there's a lot we can expect from such tech. If only they could do that for other languages, that would be really cool.
The next big thing no doubt, restart your seo...again.
Evri uses the Yahoo Boss API to index - So the scale is dependent on that API. I am guessing that must be in the process of evaluating the Bing API and depth of the news index there.
Http://www.tweetfeel.com does some pretty sentiment analysis as well.
Actually we at Evri index many thousands of news, blog and other web sources ourselves and build our own deep natural language processing based semantic index. Unlike traditional keyword search systems, our system is like an army of 7th grade grammar students armed with a really large dictionary, or knowledge base. The grammar students are basically reading documents like humans, analyzing each and every sentence, ultimately storing things like the grammatical subject, verb, object, prefix and suffix modifier information, prepositional information, as well as taxonomical information for each recognized entity (person, place or thing). The sentiment API is built on this index. It is true that in some cases, we fall back to external sources such as BOSS, but these are not currently the cases covered in the sentiment API. See my tech talk series of posts at: http://go.evri.com/rpd if you want to read more in depth about how we do what we do.
It's so coooooool.
I like it. Very much. And I can see how it has grown organically from where you where yesterday (and from before that too) which is cool.