Football fan’s ejection echoes law-enforcement plan to mine social media
A seemingly innocuous incident at a Pittsburgh Steelers game over the weekend prompted concern about the consequences of law enforcement mining social media to predict crimes.
At Saturday’s Ravens-Steelers playoff game, a Steelers fan named Jake Berlin sent out a Twitter message stating he would run onto Heinz Field if 400 people “retweeted,” or resent, his message.
“Screw it, #Steelers are losing anyway. 400 RTs and I’ll run onto Heinz Field,” Berlin tweeted.
More than 6,000 people retweeted Berlin’s message, but Berlin had no opportunity to carry out the dare.
He informed his followers he was removed from the stadium by security.
In Berlin’s case, stadium security likely was responding according to its own rules. However, the use of social media by law enforcement agencies to predict crimes could become a reality.
One recent private project aims to predict criminal activity using vast quantities of data on citizens mined from social network websites such as Facebook and Twitter.
In February, the Sydney Morning Herald reported the Massachusetts-based multinational corporation, Raytheon – the world’s fifth largest defense contractor – had developed a “Google for Spies” operation.
Herald reporter Ryan Gallagher wrote that Raytheon had “secretly developed software capable of tracking people’s movements and predicting future behavior by mining data from social networking websites” like Facebook, Twitter and Foursquare.
The software is called RIOT, or Rapid Information Overlay Technology.
Raytheon told the Herald it has not sold RIOT to any clients but admitted that, in 2010, it had shared the program’s software technology with the U.S. government as part of a “joint research and development effort … to help build a national security system capable of analyzing ‘trillions of entities’ from cyberspace.”
In April, RIOT was reportedly showcased at a U.S. government and industry national security conference for secretive, classified innovations, where it was listed under the category “big data – analytics, algorithms.”
Written by AARON KLEIN
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