For those of you who don't know, I'm still fairly new to Stanford (as well as being new to what I lovingly refer to as "library land"). When I initially started my PhD in English, specializing in Text and Corpus Linguistics and Digital Humanities, I never really thought about how text mining (and more specifically corpus linguistics) could be useful and impactful to the university research library. It also has been extremely refreshing that SUL goes another step beyond just supporting digital humanities research to actually encouraging it to occur within the library. For example, a few months ago, Chris Bourg, the Stanford University Libraries AUL for Public Service, approached me about developing a methodology for text mining acknowledgements as an alternative metric for measuring library impact.
Needless to say, the initial experiment proved extremely fruitful. Now, we're waiting to see what the rest of our colleagues in the library community think about this methodology when we present at Digital Library Federation Forum in Austin, TX, in November. Chris recently posted on her blog why this type of research and inquiry is important to libraries, and it essentially boils down to the fact that "In [Chris'] opinion, acknowledgements provide the most direct measure of the impact of library collections and services on research." As a follow-up to her blog post, I have begun a series of blog posts at A Linguist in the Library outlining the methodology we used for this research project. The series is called "A Method for Measuring Thanks," and Part 1 is titled "A Search for Thankful Candidates." In this post, I cover the intricacies of the Google Books query syntax we used for our proof-of-concept investigation. I invite you to journey on over and check it out. Enjoy!