I came across this article about the data mining team in Obama's reelection campaign. Unfortunately, the article is very fuzzy about the actual machinery of the statistical algorithms. However, it sounded as if the general techniques are known in social and political sciences. Since this is not my area of expertise, can anyone point me at (overview) literature about these kind of techniques?
That area is called microtargeting (if you would like to google for it). Campaigns are pretty secretive about their tools and procedures, so to my knowledge there is not that much published work except Hal Malchow's Political Targeting (2008) or Green & Gerber's (2008) Get out the Vote: How to Increase Voter Turnout (the latter deals more with social science aspects like what ads are effective and such).
On more technical matters the literature is even scarcer, but see, e.g, Murray & Scime (2010) or the recent paper by Rusch, Lee, Hornik, Jank & Zeileis (2012). The former use classification trees. The latter use trees, logistic models and a hybrid of trees and logistic regression. I also recall from a conference that they used random forests and neural networks and support vector machines as well, but it's not in the paper (so they might have written a different one as well but I couldn't find it). Anyway, my take away was that their hybrid trees performed on par with SVM and random forests on their data sets.