[gov2001-l] Research in political methodology...

I have a question that I wanted to ask Gary that has to do with developing research questions in methodology itself, but I figured I might as well do it here on the list in case others are interested. I have a background in some "machine learning" (SVMs, the Ising model and exact sampling, MCMC, k-nearest neighbor, HMMs), but have seen and used those methods in relation to classic problems, e.g. vision, image processing, robotics, and natural language processing. I was wondering if you could provide insight into how to bring complicated, difficult to understand methods from more "technical" fields like computer science and statistics to political methodology? I see two possible routes: (1) Do you stay on top of the statistics and comp sci literature as it's developing and then say "oh this might apply to this problem in political science"? Or (2) is it more often the case that you see some problem in the political science lit or the real world, and then you search for solutions to those in other fields? How fruitful is it to look to what others have done outside political science vs. spending the time to try to come up with your own algorithm or model? You seem to develop many methods on your own, do computer scientists every come look at your work and say, "wow, this solves a problem we've been having"? I know we're all in universities because being around other scholars makes everyone more productive, but how much do the social scientists and the computer scientists interact, for example? To give a concrete example, I've been thinking about this as I go over hidden Markov models in my artificial intelligence class (here at Brown). So if you assume that some process is a Markov process with unobserved states, one of the conical problems is to figure out from some output sequence the most likely state transitions and output probabilities. To solve this most people use a special case of the EM algorithm, which is what brought these two separate classes together for me. So I have this model that has been shown to be useful in gene prediction, cryptanalysis, and such things, and it seems like there could be some real political science applications but I'm not sure what those are exactly. This is a case where I'm operating under the first method from above-- I've found some cool solution to a problem I'm not sure I have, although I often think the second method from above makes more sense. To give a slightly more personal explanation for my curiosity: substantively I'm interested in what are often thought of as political science questions, but I get this relative joy in reading statistics and computer science articles, and I'm trying to figure out how to bring that together. You've given us a lot of intuition and skills to take substantive empirical questions and develop methods to solve the wide variety of problems we might have, but how do wake up one day with the goal of creating a new clustering methodology or trying to model something using an HMM when few people in political science even know what those are? Cheers, Zac