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The Miracle

Hello and welcome back! It’s hard to believe that two weeks have already passed and it is time for another blog entry. Although Preliminaries is alive and well and still developing, I would like deviate a bit today and talk about another project that I started a few days ago called—for the current lack of a better title—Guadalupe.

Here Guadalupe is a reference to the beloved and famous Virgin de Guadalupe, a painting that, according to legend, miraculously appeared on the maguey cloak of  Nahautl speaking Juan Diego on December 9, 1531. As close as a painting can come to being a rock star, Our Lady of Guadalupe inspired thousands of copies during the colonial period of New Spain, copious amounts of literature, entire lines of merchandise, and fervent devotion amongst the Mexican people.

I first became interested in New Spanish painting because of a class I took last spring with Alena Robin, an art historian and Assistant Professor here at Western in the Hispanic Studies department. This fall I have been taking another one of her courses called “Migration and Ethnic Relations in Colonial Latin American Art” in which we spend a lot of time discussing ethnic interactions in the American colonies and its artistic expressions. The Virgen of Guadalupe fits quite well with this theme for a variety of reasons: the location of her shrine at Tepeyac (associated with the  goddesses Tonantzin), the fact that Juan Diego was of Mexica heritage, the strong base of Nahuatl language literature documenting the apparition, the appearance of a Nahautl speaking Virgin Mary etc. So I chose Guadalupe as the subject of my term paper and began to investigate.

What I am really interested in right now is how culture works as a process, how it is coded as information and spread throughout networks, and ways to model and evaluate large cultural data sets to better understand cultural phenomenon. The Virgin of Guadalupe fits perfectly within this model because of her long-term success in Mexican culture, the quantity of cultural production centered around the miracle, and the interesting transcultural implications presented by her mythology and cult. To get a better look at the Guadalupe phenomenon, I decided to gather a big data set from her colonial era production to try to do some network analysis in Gephi. Wait a minute, a big data set for a term project? How the heck am I gonna do that? Luckily, I was able to build upon the work of other digital humanists and put together the first phase of my project in a couple hours.

Using the CulturePlex’s Baroque Art Database, I quickly located around 700 paintings with a Guadeloupian theme. From there I simply downloaded the data in various .csv files, coded up a couple quick functions in Python to clean up the data and off I went. After playing around in Gephi for a few minutes I had a nice image of the data:

 

It makes for a pretty picture, but it doesn’t really tell us much other than the basic structure of the database. One thing you notice (if you have a magnifying glass) is the large number of anonymous paintings. A little frustrating for a social networks project, but it’s the nature of the beast: most colonial paintings were not signed. Oh I forgot to mention, the schema used for this part of the visualization was quite simple. All of the Guadalupian paintings are linked to the original, miraculous painting, and the painters are linked to the paintings they signed. That is why we see the strong central prescence of “The Miracle”.

As I said before this doesn’t tell us much, so I am currently working on improving the data set through the addition of published texts with a Guadalupian theme, manuscripts gathered from the historiography of New Spanish painting, and institutional affiliations. So far I have only added a few manuscripts described in Mina Ramírez Montes’ “En defensa de la pintura. Ciudad de México, 1753”, an article detailing 4 documents uncovered by historians that all refer to the 18th century New Spanish painters’ desire for improved working conditions. These documents provide a wealth of information for network analysis, as each one is signed by a variety of painters, prominent and otherwise. After adding the documents, we start to see some more interesting results:

Here we see distinct communities beginning to form and the bridges between them. First of all we notice the “halo” around the miracle. These are the anonymous painting from the Baroque art database. Further out we see paintings with known authorship, and their painter appearing in red. Also we see the various documents in green, and their associated groups of painters. Here we begin to notice two communities: the first is generated by the earlier documents dating to the 1720’s, the second by the later documents from the 1750’s. Also we can see the bridges that form between the two groups passing through Nicolás Enríquez and Jose de Ibarra. These results–however obvious they may be–are the kind of connections and communities I hope to detect within the larger data set once it has been assembled and the quantity of information makes it difficult to detect these patterns without computational tools.

That’s it for today folks. As always I would gladly answer and questions at dbrow52@uwo.ca or @dbrownbeta

Ramírez Montes, Mina. “En defensa de la pintura. Ciudad de México.” Anales del Instituto de Investigaciones Estéticas, Núm. 78 2001: 103-128. Print.

 

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Preliminary Analysis of the Preliminaries Project

Hello! Welcome back to the Preliminaries Project blog!

This week, as promised, I would like to give you all a bit more information about the project including the current status of the Preliminaries database and the methodology used in contructing the database. However, the primary focus of this entry will be on various techniques used to analyze the Preliminaries graph, due to the fact that I have spent the last few days trying to figure out how to do this. But first let me give you a bit of background about me.

My educational background is primarily literature and linguistics. I did my undergrad work at the University of Oregon, where I studied Spanish with a fair bit of Linguistics as a secondary focus. Last year, I started my graduate work as masters student here at Western studying Hispanic Literature. My first contact with using technological means to study literary topics came last spring in in Professor Suárez’s class about the Hispanic Baroque. As a class project we started building an early version of the Preliminaries database in Sylva. I ended up doing my final project on the social networks involved in the production of early editions of Don Quixote, and I haven’t looked back. Last summer, I began officially working here at the Culturplex Lab on the Preliminaries Project. So to make a long story short I am a rookie when it comes to digital humanities, computer modeling, and programming. This fall I have been taking a class that focuses on Python, a high level programming language that is popular amongst scientists of all types, and also a Coursera course about social network analysis. I am just learning how to use this technology, but I hope I can share some of this learning process with you and in the end maybe everyone will benefit. Okay enough about me…let’s get back to the project.

As I mentioned before the Prelims Project is ongoing, and although it isn’t 100% complete, the database is sufficiently devoloped to begin doing a bit of analysis. Currently the first editions list (Duque de Lerma, 1598-1618) constists of 330 editions, out of which I have been able to obtain 228 scanned copies of preliminary sections, approximately %70, which isn’t bad considering that these texts were published 400 years ago. Of these scans, around 120 have been entered into the database, producing a graph with 1612 nodes and 3472 relationships. Rendered in Gephi using the built in YifanHu’s Multlevel algorithm, colored for modularity, and sized for betweenness centrality, the graph looks like this:

This visualization is nice because you can see the general structure of the graph and the coloring gives you a good idea of the communities within the the network as a whole. However, the amount of information presented here is overwhelming, so I have been looking for some ways to control the visualization and the information on which it is based to allow for some detailed comparative analysis.

One of the nice features of Gephi is that it has a variety of built in filters to allow the user to limit the information that appears in the graph. Something that we are interested in regarding the Prelims Project is the community structures within the graph. Let’s use a filter to see the modules of various famous writers of the period:

First Miguel de Cervantes, author of Don Quixote

Then Lope de Vega, author of the Comedias

As you may imagine, this type of filtration is crucial for analysis. It allows us pick apart the graph and study the elements in a controlled and manageable fashion.

There is another type of subset within a graph called the Ego Network. These are based on direct conections between a node and its neighbors. Although Gephi also has an filter for Ego Networks, I encountered a small problem here: Gephi only allows filtering for up to three degrees of seperation. This presents a challenge with the Preliminaries graph due to the schema design for the database.

In order to establish a connection between the author and an edition there are two steps: Author->Obra, Obra->Edition. This is due to organizational/editorial concerns that I hope to address in the next blog. Furthermore, for the author to be related to the people involved in the approval, licensing, and publication of an edition, two more steps are required e.g Edition->Approval, Approval->Censor. Therefore to establish what I call a Publication Network, somewhat equivalent to an Ego Network, I need to be able to find neighbors for up to four degrees of seperation. Thankfully, Gephi includes a scripting console based on the Python programming language. Using functions based on the following patterns I am able to mimic the filtering abilities of Gephi and create a way to isolate and compare subsets of the graph in order to generate these Publication Networks:

 

 

 

 

 

 

 

 

 

It is also important to note that it is necessary to combine the subsets generated by these functions, which I have done using the following function “completelist”, and then to make sure there are no stray ‘NoneType’s or duplicates, which I have done with  “masterlist”:

Then, using the subsets generated here I can color and size the Publication Networks using the following functions:

I can also find the intersections of various Publication Networks using the following function:

Thus, using a very basic knowledge of Python I am able to manipulate the graph and compare any subsets of nodes that I would like.

An applied example of these functions would be the following:

Publication network of Bernardo de Balbuena, author of Grandeza mexicana: Red

Publication network of Juan de Torquemada, author of Monarquía Indian: Blue

Their intersecting Publication Networks: Yellow

That’s it for today folks. Over the next week and a half I hope to generate some definite results to talk about and some more refined visualizations using my newfound techie skills.

Hope to see you next time around. For more information you can always email me at: dbrow52@uwo.ca or follow me on twitter @dbrownbeta

 

 

 

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