The Pentagon Enters the Social Web With a Call for Memetrackers

The Department of Defense's tech incubator is looking for a few bright minds to revolutionize how the military uses social networks

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Do you spend hours a day on Facebook? Can you sniff out Twitter memes before they become full-fledged trending topics? Good news: the Pentagon is looking for someone like you.

The Defense Advanced Research Projects Agency (DARPA), the DoD progenitors of revolutionary tech like passive radar and the Internet, is calling for research applications of social media to strategic communication. According to an agency announcement (PDF), DARPA is looking to shell out $42 million in funding for "innovative approaches that enable revolutionary advances in science, devices, or systems." The general goal of the Social Media in Strategic Communication (SMISC) program is to develop a new science of social networks built on an emerging technology base.

In short, the Pentagon wants to up its intelligence game to keep pace with the constantly expanding, interwoven latticework of connections in the social space. The military wants to be able to track the formation, development and spread of ideas and concepts, use linguistic clues to ferret out purposeful or deceptive misinformation, and use sentiment analysis and opinion mining to extrapolate, for example, where the next Arab revolution might take place, or identify credible (or debunked) threats reverberating across cyberspace.

This certainly isn't the federal government's first foray into using social media for intelligence gathering. The FBI began using social networking sites to gather information about the whereabouts of fugitives, even combing through Facebook and Twitter for clues as to the location of notorious Boston gangster James "Whitey" Bulger. But as David Streitfeld reported in the New York Times, such methods of information collection and analysis are far from systematized:

Social networks can allow the military not only to follow but also to shape the action. In its 37-page solicitation, Darpa described how a would-be high-technology lynching was foiled: "Rumors about the location of a certain individual began to spread in social media space and calls for storming the rumored location reached a fever pitch. By chance, responsible authorities were monitoring the social media, detected the crisis building, sent out effective messaging to dispel the rumors and averted a physical attack on the rumored location."

(Is this a reference to Osama bin Laden or someone much more obscure? Were the "responsible authorities" trying to put off an attack because the individual was not at the location, or because he was? Darpa officials did not return e-mails requesting comment.)

The crisis was formed, observed, understood and diffused entirely within social media, the solicitation noted. But the success of the authorities was a fluke, the result of "luck and unsophisticated manual methods."

Luckily for DARPA, applicable research into semantic analysis of the social Web has been underway for years in the private sector. At Indiana University in Bloomington's School for Informatics and Computing, the independent research of Professors Johan Bollen, Fil Menczer, Alex Vespignani, and Sandro Flammini at the Center for Complex Networks and Systems has become increasingly intertwined and integrated over time into a discipline they call "computational social science." Menczer heads a project called Truthy, which tracks the flow of information (and misinformation) over social networks and has been used to ferret our search engine spamming. Vespignani uses mood-tagged Twitter messages to anticipate the spread of biological agents during diseases outbreaks. Bollen's was leading a project focused on tracking the correlations between messages sent in the social space -- tweets, status updates, and the like -- and fluctuations in the Dow Jones Industrial Average. Bollen found that by categorizing millions of Twitter posts into various mood categories (happiness, kindness, alertness, sureness, vitality and calmness), he could anticipate fluctuations in the Dow with an 87% chance of accuracy. Bollen's research garnered the attention of the New York Times Magazine, which helped introduce the idea of social media as social index to the general population.

Presented by

Jared Keller is a former associate editor for The Atlantic and The Atlantic Wire and has also written for Lapham's Quarterly's Deja Vu blog, National Journal's The Hotline, Boston's Weekly Dig, and Preservation magazine. 

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