Your mom isn’t the only one interested in learning from your tweets.
Federal government agencies and companies have been pulling out mentions of key people, places, and things from social networks, media outlets, and other sources in more than 200 languages with help from a startup called Babel Street.
Now the technology could find wider use as a result of $2 million in funding flowing to the startup. The money, which will go toward sales, marketing, and product development, comes from angel investors. A filing yesterday with the U.S. Securities and Exchange Commission disclosed part of the round.
Read the funding as how important it is for governments and businesses alike to be able to go deep into data to solve global problems. This is a multilingual play, after all.
Look at how Babel Street’s software went to work after last year’s Boston Marathon bombings. It enabled users to narrow down a search for messages coming out of the small geographical area near the attacks, Jeff Chapman, Babel Street’s chief executive, said in an interview with VentureBeat.
“Within minutes of the bombing going off … our system dropped a bubble over the bombing, and we got geo-enabled data there,” Chapman said. “We rewound 24 hours, showing them [researchers] what the data was leading up to it. … We were able to pull his [Dzhokhar Tsarnaev’s] VK [European social media] account and basically create this social nodal analysis very quickly for decision-makers.”
From there, it was possible to create a profile of Tsarnaev based on the references he made to other people, his communication style, and the subjects he discussed most. The magic comes when you align that profile with those of terrorists from the past, said Chapman, who previously worked inside the U.S. Naval Criminal Investigative Service.
Babel Street can do that because it knows how words and names are spelled in dozens of languages.
“I have the entity Derek Jeter in over 40 languages,” Chapman said. “I have Pizza Hut in over 60.” The data is preloaded in Babel Street, so searching across languages can happen fast. And search process is easy; it’s a matter of using drop-down menus, said Chapman, who sold his company Harbinger Technologies Group to data company Acxiom in 2007. Harbinger dealt in homeland security and counterterrorism.
Babel Street was originally named Agincourt Solutions. It opened up in 2009, after Chapman observed that some people weren’t getting as much out of publicly available data as they could.
“It’s a huge gap that we’ve got to get good information in the hands of these people that are going into harm’s way,” Chapman said.
Users can create dashboards and alerts and export data from Babel Street’s software, which is available on a monthly subscription basis.
Investors have shown interest lately in backing startups that draw valuable data from complex text, including AlchemyAPI, Idibon, and Synapsify.
Companies like Bitext, Clarabridge, Luminoso, Semantria, and Synapsify also do text analytics and sentiment analysis. Researchers at IBM have also been working on new ways to analyze text inputs, too.
But those companies don’t show up very much on Babel Street’s radar; rather, it’s players like Crimson Hexagon and Salesforce.com’s Radian6 that do, Eric Bowen, Babel Street’s executive vice president for training and analysis, told VentureBeat.
Babel Street is based in Reston, Va., with around 10 full-time employes.
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