OK, it’s hard for me to admit this, but in going through Birnbaum’s post on Regular Expressions, my eyes quickly glazed over and he lost me in about three paragraphs. This is exactly the sort of thing I have been trying to avoid all of my life–that’s why I’ve always used Macs!!! OK, I know it’s not really that complicated, but having never done this kind of work before, I definitely feel like a fish out of water. But, that’s why I’m here in this class, to get my hands dirty.
On the other hand, the digitization and metadata article from Stanford.edu was concise, and easy to grasp. The “Overview of Text Analysis” was similarly clear and distilled. The Deegan and Tanner chapter likewise is suitable for a newbie like me, and though I am familiar with much of the material in it, I appreciate that the authors assume that the reader knows nothing.
The Ted Underwood blog is great. I like two things he said: “Yes, at bottom, text mining is often about counting words. But a) words matter and b) they hang together in interesting ways, like individual dabs of paint that together start to form a picture”, and “I think that word [mining, as in text mining] accurately conveys the scale of this enterprise, and the fact that it’s often more exploratory than probative”. He has also convinced me that it will be necessary to learn how to program if I am to do this kind of work in depth.
As far as my own data is concerned, well the fact is I don’t have it yet. I hope to be working with images, specifically jazz album covers, as cultural artifacts. How to find it, prepare it, visualize it, etc., is what I am hoping to learn this term.