Friday, September 3. 2010
Good article in The Economist that looks at the wide range of datamining activity on Social Nets - firstly, it breaks marvellously benign new ground:
..broadening data mining to include analysis of social networks makes new things possible. Modelling social relationships is akin to creating an “index of power”, says Stephen Borgatti, a network-analysis expert at the University of Kentucky in Lexington. In some companies, e-mails are analysed automatically to help bosses manage their workers. Employees who are often asked for advice may be good candidates for promotion, for example.
Crime can be reduced....
Ellen Joyner of SAS, an analytics firm based in Cary, North Carolina, notes that more and more financial firms are using the software to uncover fraud. The latest version of SAS’s software identifies risky borrowers by examining their social networks and Internal Revenue Service records, she says. For example, an applicant may be a bad risk, or even a fraudster, if he plans to launch a type of business which has no links to his social network, education, previous business dealings or travel history, which can be pieced together with credit-card records. Ms Joyner says the software can also determine if an applicant has associated with known criminals—perhaps his fiancée has shared an address with a parolee. Some insurers reduce premiums for banks that protect themselves with such software.
The police department of Richmond, Virginia, has pioneered the use of network-analysis software to predict crimes. Police officers know that crime increases at certain times, such as on paydays and when there is a full moon. But the software lets them analyse the social networks around suspects, such as dealings with employers, collection agencies and the Department of Motor Vehicles. The goal, according to Stephen Hollifield, the department’s technology chief, is to “pull together a complete picture” of suspects and their social circle.
Party plans turn out to be a particularly useful part of this picture. Richmond’s police have started monitoring Facebook, MySpace and Twitter messages to determine where the rowdiest festivities will be. On big party nights, the department now saves about $15,000 on overtime pay, because officers are deployed to areas that the software deems ripe for criminal activity. Crime has “dramatically” declined as a result, says Mr Hollifield. Colin Shearer, vice-president of predictive analytics at SPSS, a division of IBM that makes the software in question, says it can largely replace police officers’ reliance on “gut feel”.
Secondly, it finds the real influencers, good and bad:
TELECOMS operators naturally prize mobile-phone subscribers who spend a lot, but some thriftier customers, it turns out, are actually more valuable. Known as “influencers”, these subscribers frequently persuade their friends, family and colleagues to follow them when they switch to a rival operator. The trick, then, is to identify such trendsetting subscribers and keep them on board with special discounts and promotions. People at the top of the office or social pecking order often receive quick callbacks, do not worry about calling other people late at night and tend to get more calls at times when social events are most often organised, such as Friday afternoons. Influential customers also reveal their clout by making long calls, while the calls they receive are generally short.
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Network analysis also has a useful role to play in counterterrorism. Terror groups are often decentralised, so mapping their social networks is akin to deciphering “a big spaghetti picture”, says Roy Lindelauf of the Royal Dutch Defence Academy, who develops software for intelligence agencies in the Netherlands. It turns out that the key terrorists in a group are often not the leaders, but rather seemingly low-level people, such as drivers and guides, who keep addresses and phone numbers memorised. Such people tend to stand out in network models because of their high level of connectedness. To find them, analysts map “structural signatures” such as short phone calls placed to the same number just before and after an attack, which may indicate that the beginning and end of an operation has been reported.
Marvellous, I hear you say - what can go wrong? Well, nothing except the amount of data about you that they want, and all the other things they can predict with it - like your infidelities for example (believe me, you can...). But it is not going to go away:
The market for such software is booming. By one estimate there are more than 100 programs for network analysis, also known as link analysis or predictive analysis. The raw data used may extend far beyond phone records to encompass information available from private and governmental entities, and internet sources such as Facebook. IBM, the supplier of the system used by Bharti Airtel, says its annual sales of such software, now growing at double-digit rates, will exceed $15 billion by 2015. In the past five years IBM has spent more than $11 billion buying makers of network-analysis software. Gartner, a market-research firm, ranks the technology at number two in its list of strategic business operations meriting significant investment this year.
And its getting easier - 5 years ago I needed all I'd learned in an MSc in Engineering doing what what was effectively Stats and Operations Research, but now:
A decade ago IBM employed experts with PhDs in mathematics to study social networks, according to Mark Ramsey, the firm’s head of business analytics for eastern Europe, the Middle East and Africa. Today, college graduates can operate analysis software handling enormous quantities of data. Bharti Airtel employs only about 100 analysts to keep tabs on its 135m subscribers.
I was at an early futurology session on this about 10 years ago, the endgame was succinctly described as being able to predict the "Net Present Value of your Future Spend".
You have been warned........
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