Big Brother 101

Hub Bubs The people seemingly at the center of social networks-the hubs with the most connections-may not be so central after all. The highly connnected Diane appears to be the main hub here, but no real damage is done when she leaves the picture, below (one reason you never want to be a Diane at your workplace).

Instant Expert:

By some counts, government snoops are sifting through data from a billion or more phone calls and online messages daily. What might they be looking for?

• WHO: The National Security Agency and other intelligence groups
• WHAT: Processing and connecting data from phone calls, e-mails, online postings and financial transactions
• HOW: Using social-network analysis (the study of how people interact) and data-mining techniques (such as pattern-recognition algorithms) first used for artificial intelligence and consumer marketing
• WHY: To help uncover the structure of potential terrorist groups-far too secretive and dispersed to locate with traditional detection techniques-and decode their intentions

FAQs

Does this stuff REALLY work?

Data-mining techniques regularly help investigators identify credit-card-fraud and money-laundering patterns. And research in 2002 by social-network-analysis pioneer Valdis Krebs showed how the 9/11 plotters were all linked (some hijackers were separated by as many as 10 degrees, he found), but that was, alas, after the fact. Predictive data mining to preempt terrorist networks or activities hasn´t been publicly proven so far.

Why would the feds want my phone records?

To cast the widest possible data net. What seem like coincidental events can offer hidden ties. If person A makes a phone call to person B, and half an hour later person C transfers $10,000 to the account of person D, all four of them could be in the same gang (or not). Analysts also chart what terrorists have done in the past-phoning Afghanistan, cashing checks from Saudi Arabia, enrolling in flight school, buying fertilizer-to sniff for people who might fit similar pattterns now. Yet predictive software must be â€trained†with good sample data or the algorithm might not work (witness 2002´s â€terror pizza†mishap: the idea that repeatedly ordering a pie with a credit card somehow indicated enemy-of-the-state status). Some data miners believe that just about everyone has to be included because you don´t want to chance missing anybody in that huge pool of American averageness.

So what´s the big stink all about?

Besides, um, the Constitution? Intelligence pros themselves argue fiercely over how widely to look for suspects. Some say all that extra data is merely noise that too often sends the feds running down the wrong paths. Better to start data-diving with known perps, insists Naval Postgraduate School counterterrorism expert John Arquilla: â€Pulling on a string, instead of just casting a net to see what comes up.â€

Continue on to the next page to see how social networks can uncover the true mastermind of a group.