Last week I looked at some of the clusters of words that fluctuate together across narrative time in the Lab’s corpus of ~27k American novels. A lot of these are pretty semantically “legible,” in the sense that it’s not hard
I wanted to pick back up quickly with that list of the 500 most “non-uniform” words at the end of the last post about word distributions across narrative time in the American novel corpus. Before, I just put these into
Over the course of the last few months here at the Literary Lab, I’ve been working on a little project that looks at the distributions of individual words inside of novels, when averaged out across lots and lots of texts.
Not for the first time, I find myself wanting to know how big the field of the novel is. Granted, finding the precise number of novels published in English is impossible. And even if we had an exact figure, the
This was my sophomore summer with the Literary Lab. I started the summer ready to capitalize on my veteran knowledge and pick up where I left off. I did just that when I spent the the first weeks of summer
I first became familiar with the Literary Lab when I took a class on literary text mining in R with Mark Algee-Hewitt last winter. From discussing the philosophies behind the digital humanities to constructing cluster dendrograms (plus lots of other
On my first day of work, I looked up the term “operationalize” in the dictionary. A mixture of curiosity and sheer pragmatism led me to do this; after all, the project I was about to embark on aimed to “operationalize
In recent months we’ve been working on a couple of projects here in the Lab that are making use of the Extracted Features data from HathiTrust. To help kick off the lab’s new Techne series, I wanted to take a look at some of the programming patterns we’ve been using that make it easier to work these kinds of large data sets – namely the “Message Passing Interface” (MPI), a set of semantics for spreading out programs in large computing grids.
The humanities are used to feeling embattled, and, consequently, to making excuses for their existence. We should be allowed to study literature, one such line of argument goes, because reading and writing make students better employees or better citizens or more empathic human beings — because literature has some merit that is not merely aesthetic.
Often, the most exciting moment of a Lab project occurs when our research takes an unexpected direction: we thought we were doing ‘a’, but it turns out that all along we’ve been doing ‘b’ (or, more often, should have been doing ‘b’). The realization that we’ve discovered something unexpected, the ability to be guided by the research and its results: these are what differentiates a Lab project from the traditional pursuits of the humanities.