I realised today that I could have titled this “Life, the University, and Everything”, which would have worked a lot better. Hey ho.
The grandiose title of this piece could be read as a sign that I’m going to write about things other than relevant to the course. In general, I’m going to steer clear of that sort of approach in this piece of text. I am slightly tempted to do a cross-comparative chart of my mental state versus the deadline of this module, but the time for that sort of navel-gazing isn’t now, and this isn’t really the place. So, what to do with such a grandiose title?
I know: we’ll talk about Lev Manovich.
Manovich is famous for putting together two things. First, his book, the Language of New Media, which was an early foray into series notions about the academic reception of New Media artworks. It’s aligning of the concepts behind computing as being analogous to early cinema was a masterstroke of metaphor, allowing humanities departments the world over to finally get their head around the fact that yes, really, we are going to be using these computer things for artistic purposes and we better get used to it.
The other thing that Manovich is famous for is his de/reconstructed film software “Soft Cinema”, which puts into practice the more theoretical notions that he talks about in his book. This work was, in fact, shown in the Baltic at an early stage in it’s gestation, where I walked in and then promptly walked out again (having a very low tolerance for the sort of abstract narrative found in most art films).
But these are not the features of Manovich’s practice that I’m going to discuss here. In his recent work, Manovich has looked at the way that society is pressurising all information onto a digital plane, and concluded that as more raw data is available in this form, it is the practice of data-mining that will become valuable. This is a conclusion actually being reached independently in several different structures at the same time, by researchers working in different fields.
This polyphyletic idea is ideally suited to Manovich’s position as somebody who can talk about the practice of art and computers in a way that those working in other fields can’t. For instance, whilst both Martin Wattenburg and Ben Fry are creating, promoting, and even working as artists in these fields, they still do not have the necessary academic chutzpah to propel the idea under discussion out of the ballpark. They are, essentially, knocking the idea around between a few like-minded friends.
Franco Moretti is not a like-minded friend, nor is he particularly interested in what we would term “New Media” (from what I can make out, which should be regarded as limited). However, what he is interested in, as a leading left-wing literary critic, is a method of understanding texts. And, as Manovich would point out, these texts are merely data awaiting transmutation into a computerised form. Therefore, coming to the point and the birth of yet another instance of our polyphyletic idea, Moretti suggests the use of quantitative data analysis for literature in his book “Graphs, Maps, Trees”.
I find the fact that infovisualization is being suggested as a research tool in the humanities as particularly interesting, and when I attended a recent afterparty for a Newcastle University conference on Crime Fiction I had a chance to quiz those doing stylistic analysis of texts in other fields. It was regarded as impossible that a visual program could be analysed by a computer (not so, either by using jit.cv or by web services such as Mechanical Turk). But I’m not sure that these people were participating in leading edge research, and besides, I was being plied with mohitios at the time.
The final point of this is, however, that there will be an expanding bubble of interest around these themes of data-mining and the humanities, and that Newcastle University already has some projects and researchers that are interested in this field (by which I am not referring to myself, but rather people working within the English department whom I’ve met very briefly). There needs to be a way of gathering the tools, or creating accessible tools for these researchers, and as soon as possible, so that Moretti’s idea of quantitative tools for qualitative purposes can become a reality.
Having said that, I’m now ready to share my own set of quantitative tools. Be aware that this is a rough and ready – but working – version, and merely produces a small line-graph and a text files that counts specific words. In the next section of this (essay? Series of blog posts?) I’ll discuss the road not taken, by which I mean the false starts and horrific crushing disappointments of working in code.
