Well folks it’s that time of the year again, only three weeks left in the term and final essay deadlines are looming in the near future. I haven’t had much time to focus on Preliminaries, but I’ve finally started to make some headway on my other projects. To tell the truth, all of my academic endeavours this semester are based on the Prelims Project one way or another; I guess you could say I’ve been training, getting ready for things to come. One of the primary concerns of Prelims is efficiency in data set compilation and model building—a daunting task—especially when you have to work with copious amount of information gleaned from scanned 17th century texts. While we will always have to read the preliminaries section of the text and manually compile the data that will become nodes and edges, other parts of the process should be able to be performed almost automatically using minimal human labour. So, to make a long story short, I am basically focusing this term on building skills I need to advance the Preliminaries Project efficiently and, I must admit, having some good fun along the way. Hence the Python, the Gephi, the endless graphs and the current single-mindedness of the Prelims blog—hey the blog is called Preliminaries Project. Who knows what comes next, only time will tell…but for now, graphs and Python. So here we go…
Last week we talked a bit about the Virgin of Guadalupe, so this week I would like to talk a bit about another class I’m taking called La Máquina Cultural. This course is team-taught by Professors Juan Luis Suárez and Rafael Montano and designed and instructed by Juan Sánchez, a fellow Ph.D. student and amigo here at Western. The class is based on a fantastic new approach to understanding Latin American texts as a highly heterogeneous corpus that emerges from the cultural exchanges that take place at encrucijadas literarias, or literary crossroads, which represent cultural interaction between diverse cultures on a global scale. This concept is represented graphically and figuratively as the Máquina Cultural:
In the center of the machine is the diverse corpus of Latin American literature. The second largest pinions are a kind of category or grouping within the corpus. The outer ring represents the texts, or cultural objects. The idea is, if you move one pinion, you move them all, and interaction occurs all throughout that cultural system. More information about the course can be found at its various Yutzu’s.
As part of the requirements for the class, each student is required to invent a new model of the Máquina and propose a new pinion. More than a homework assignment, this process of genesis seems to take on a symbolic discourse: a new generation of academics trying to break free of traditionally boundaries and create innovative ways to understand the cultural process. It’s happening. It’s all over the Internet. And, fortunately or not, we are part of it.
What I would like to show you tonight is an early version of my model for the new Máquina Cultural. I decided to stick with the basic model designed by Juan—I find it very thought provoking—with a few little changes. First, I decided to move away from the mechanical image of the machine and move to a more organic (network based) model. Second, I wanted to symbolically represent human interaction with the literary corpus. Third, I decided to call the center pinion “Cultura Colectiva”. Finally, I also created a new pinion called “Tierra Adentro”, which I will discuss in more detail later this week in my Spanish language blog Por la máquina.
So how did I do this? With Gephi and Python of course! (complete version of Python script at this gist)
Using the Python module NetworkX I created the unique nodes (categorical pinions), one by one, and then generated the core of the graph by connecting all of the categorical pinions to the “Cultura Colectiva” node:
Then I used a couple of simple loops to generate chunks of node ids, and link up the edges in an orderly fashion:
The general schema of the graph is the following:
‘Cultura Colectiva’->’8 unique nodes’->’15 object nodes’ per unique node->’30 agent nodes’ per object node . This ends up being 9 core nodes, 120 object nodes, and 3600 agent nodes: 3729 nodes, 3728 edges.
Here is the graph rendered in Gephi with the Fruchterman Reingold layout algorithm and sized for betweenness centrality:
[‘Cultura Colectiva’.color = blue, ‘Categorical Nodes’.color = purple,
‘Obejct Nodes’.color = green, ‘Agent Nodes’.color = blue]
I like to think of this model more as the “Cultural Interface” than the “Cultural Machine”—a moment frozen in cultural time—where humans interact meaningfully with a cultural object, an interaction that receives and informs the collective cultural knowledge as it flows through networks of people and places and objects and time…pretty far out…I know.
Anyway this blog is getting long and the night of the busy grad student is still young. Until next time @dbrownbeta