Data Mining 101

Tom Owad over at Applefritter has a nice simple example of the kind of homebrew data aggregation that’s possible with just a little bit of programming knowledge and a home internet connection.

The thing that scares me about data mining is not that super-secret information about me is revealed — my Amazon wish-list doesn’t contain anything I’d be embarrassed or concerned if it was seen by any of my friends or for that matter 99% of the other people in the world. And odds are good that anyone bothering to look me up by name or go to my website will fall into that category. The trouble is that if I pop up in a trolling-expedition at all it’s much more likely the troller is among that 1% of the people that I would be upset about reading my wish-list. Ed McMahon doesn’t mine the Internet to pick winners of the Publishers Sweepstakes, but over-zealous FBI agents do look for people promoting the wrong politics, companies look for suckers to blast with seemingly perfect-for-you product announcements, con artists look for rich recently-widowed women above a certain age, and pedophiles look for young latch-key kids with their own webcams.