April 15th is the deadline for proposals for the first ever DH SoCal Research Slam.

Location: California State University, Northridge
Date: May 4, 2013
Deadline for Proposals: April 15, 2013

DH SoCal is a network dedicated to building community and collaboration amongst digital humanists in Southern California. On May 4, 2013 we are holding our first research slam at California State University, Northridge. This one-day event will be designed to showcase Digital Humanities work and work in progress by, and to create opportunities for interaction between digital humanists from around the region.

We invite proposals for poster presentations, short talks, and issue-based discussion panels in any area of the Digital Humanities. To propose a topic, please fill out the submission form by April 15, 2013.… Read more…

I’m a little under the weather, so this post might not be as coherent as I’d like, but I want to get it up before I get overwhelmed by the what is likely to be a very busy few days.

Over the weekend, I decided that an interesting exercise for my students reading the Alliterative Morte Arthure would be to have them compare two very different approaches to the poem, Kateryna Alexandra Rudnytzky’s article on Arthur’s battle with the giant of Mont Saint Michel, and Patricia DeMarco’s “An Arthur for the Ricardian Age”. The one examines the poem in terms of the transformation of its source material and connections with literary analogues; the other focuses on the poem’s engagement with military history. Both approaches add depth to our understanding of the text and its place in the medieval literary and cultural world, yet they are based on exactly the sorts of observations that students cannot make because they have not had the opportunity to read widely. Students are forced to read a few texts, those for which there is time during a single semester, in a virtual vacuum. Naturally, that’s why we have professors–to assign secondary literature and to draw students’ attention to this type of knowledge in class.… Read more…

I’ve been meaning to post something about William Pannapackers’s article “Stop Calling It ‘Digital Humanities’” for a couple of days, but my teaching schedule is stacked towards the beginning of the week, so it had to wait. Now that Rafael Alvarado’s response has appeared as an Editor’s Choice on Digital Humanities Now, I thought I’d set my fingers to typing.

Pannapacker laments the way that pedagogy has lagged behind research in the development of the Digital Humanities His main point seems to be that the identity of the Digital Humanities has developed so one-sidedly around research activity that it is difficulty to transfer to more teaching-oriented institutions, whether that means faculty lacking the resources to engage in Digital Humanities scholarship or faculty wishing to teach something called the Digital Humanities to their students.

Pannapacker is not advising us to give up.* Overall, his suggestions are helpful hints for how to overcome the barriers in certain kinds of institutions. But therein lies the problem. Pannapacker has primarily the small liberal arts college in mind, and he is unconsciously making the same mistake he critiques—proposing that the Digital Humanities be defined in terms of the mission of a particular type of institution.… Read more…

Many of my students ask me why I drink those little cups of espresso. I’m told that there are debates going on outside the classroom. So I thought I’d produce some kind of public explanation to put the speculation to rest. So here it is.

Espresso is a term used only in English-speaking countries. It is short for caffè espresso: coffee made expressly (i.e. upon request). It is made expressly for you when you order it. In Italy, the idea of pre-brewing coffee is unheard of. So ordering a caffè in Italy will always get you what Americans call “espresso”. In other Mediterranean countries you may get something a little different, depending upon the technology used to produce the coffee. But it is generally made to order.

Why the small cup? It’s sometimes called a demitasse. That’s French for “half-cup”, but it’s a particularly Italian style of drinking coffee based on an invention by Luigi Bezzerra by Desiderio Pavoni at the beginning of the twentieth century. Jimmy Stamp at Smithsonian.com describes them as the “the Steve Wozniak and Steve Jobs of espresso”. The process used pressure to force hot water through fairly finely ground coffee beans in order to brew quickly and dispense directly into the cup.… Read more…

This is a follow-up to my earlier post on Topic Models and Spelling Variation: The Case of Early Middle English. There I discussed the challenges of generating topic models of texts with non-standardised spelling where topics did not merely correspond to texts. In any given model, differences in the spelling systems of two texts will cause the generated topics to be prominent in some texts and effectively non-existent in others, whereas other topics will be non-existent in the former and prominent in the latter. Topics are thus essentially orthographic patterns, rather than rhetorical discourses or indicators of subject matter. My initial experiments showed that some linguistic smoothing–admittedly,  a questionable form of textual deformance–can help address this problem, along with increasing the granularity of the model by breaking texts into small chunks. Chunk sizes of about 1000 words began to reveal the sorts of patterns I was looking for: cases where individual topics had high prominence in parts of more than one text. But I speculated that chunk sizes needed to be still smaller in order make these patterns more noticeable. A second reason for using smaller chunk sizes is that it becomes much easier to make the leap back from distant to close reading.… Read more…

Topic Modelling has developed quite a following in the DH world, but it still has a long way to go before it proves itself a reliable method for literary research. (Caveat: I have not yet read Matthew Jockers’ soon-to-be released Macroanalysis, which may answer many questions about how to use topic modelling to study literature.) As far as I can tell, topic modelling was originally tested on materials that, although diverse in subject matter, were fairly homogeneous in language. Literary language is problematic for topic modelling not so much because it contains more ambiguities or fuzziness than, say, scientific journals but because the types of questions literary scholars ask tend to probe at these aspects of language. There’s no reason why we should expect a single, and fairly new, computational method to provide miraculous insight into questions that sustain whole disciplinary fields, and neither is that a reason to assume that it can provide no insight at all. Topic modelling has already shown particular importance in the area of literary history, as can be seen from the work of Jockers’s work, as well as that of people like Ted Underwood and Lisa Rhody. But the results that they have made available share one thing in common with the various topic models of scientific journals, Day of DH posts, PMLA articles, and the like.… Read more…

This year’s Thanksgiving word cloud includes both Facebook and my Twitter feed.

Noticeably absent this year is the word “bacon”.

And, for good measure, here is a topic model of the tweets and posts:

1. I’m canyon things man cuteness blog ol drop teens gourd
2. you’re lovely hike home family kill center orangutanes morning daily
3. thanksgiving love turkey join audience kennedys infotech anonymous open driving
4. kill history started jugar marylebone brightest uk leave topic twitter
5. happy monrovia post reading move pie cat puddytat beagles
6. day 1st work hiking eating dogs participation gustar espa obama
7. thankful friends house make grading awesome head miss family dpla
8. today beautiful turkeys year media con project triumphs articles tea
9. la weather london dinner survived grateful marblehead hackfest workshop en
10. park gobble beginning good kittens feasting te cnn touch wouldn’t

Suggestions for topic labels welcome.

Update: I was surprised to find that this post appeared on DH Now Unfiltered, so, given the increased traffic, I thought I’d better provide some explanation. I am trying to make this a regular tradition, after having produced a word cloud of last year’s Facebook posts on Thanksgiving. All the posts are only those by me or my friends, and this year’s Twitter feed includes only tweets by me or those I follow (plus the sponsored posts).… Read more…

I really think this is a fabulous presentation on the nature of digital literacy:

Taking a break from my re-working of past posts on computational approaches to text analysis, I want to express a plea for attention to be paid to small data and for small data to form part of the larger conversation about quantitative analysis in the Digital Humanities. As the range of digitised materials expand through the proliferation of digitised print materials and born digital texts, big data has come to represent the opportunity for innovation in the Digital Humanities. For those of us who work in areas that have corpora that are restricted in size (medieval English literature, in my case), this represents a problem. How can those of us working in fields that employ these corpora participate in the growing conversation? Are the Digital Humanities doomed to experience a divide between those who do distant reading on “big data” and those who do close reading through markup and editing of smaller numbers of texts? One way the latter group can bridge the divide is by generating lots of metadata. But that only goes so far and doesn’t address some of the analysis of language being done through techniques like topic modelling and the like.

Small data is very useful because it throws into relief some of the same theoretical questions that (in my view) have yet to be sufficiently addressed in approaches to “big data”.… Read more…

Note: This post is part of a series reworkings of materials originally written between 2009 and 2012. A description of the nature and purpose of this project can be found here.

Still in September of 2009, I was speculating that comparing manuscript variations would be one of the most popular uses of Lexomics. I was definitely wrong. To date, the Anglo-Saxon Penitentials are the only texts we have subjected to this kind of analysis, and the verdict is not yet in. The process of (digital) manuscript collation is a real challenge, particularly in collating in such a way that one can extract lined up token lists for word frequency analysis. I haven’t seen what the latest version of Juxta can do; I probably need to make time for an experiment in the future. Sadly, I am not currently working on any texts that survive in more than two manuscripts, so this may have to wait.

As my speculation about collation more or less ground to a halt, I was continuing to think about the problem of representing meaning through cluster analysis. In addition to the problem of editorial influence, there is a question over what textual phenomena are being measured by the algorithm.… Read more…