Working with Sci2 and Cytoscape

Weighted Bipartite Network -- Thickness of line indicates relative number of contributions

This peculiar, fish-like graph is the result of another morning's efforts to get my initial data into a meaningful and interpretable form. Using the Sci2 Tool (developed at Indiana University for use in analyzing scientific data and co-author networks in scientific literature), I loaded a .CSV file containing my bipartite network data and edge attributes (i.e., weight = # of contributions). I then extracted a bipartite network from this file and used the Cytoscape visualization tool to begin looking at the results.

While the workflow just described might sound straightforward enough, I did run into trouble loading the edge attribute data into Sci2. Failing to find a solution, I ended up entering the data manually in the Cytoscape application, a process made somewhat easier by the fact that I could sort the edges into a list roughly similar to the list contained in my original .CSV file.

Once the data was entered, I could begin the fun part of manipulating the visualization into something that was readable. So, for example, I set the poet and journal nodes to be different shapes and colors. The yellow triangles on the outer rim represent the journals and the green squares just to the right of center represent the 25 poets who makeup my initial database. I then set the thickness of the lines to reflect their weight, with the thinnest lines representing a value of 1 and the thickest representing a value of 48. I also split the journals so as to see more readily which of them had the most contributors in common. Besides 「学校」, of course, these journals included 「詩神」, 「太平洋詩人」, 「暦程」, and 「弾道」.

As I did these manipulations, a couple of questions and ideas arose as to what we might be able to learn and display just at the level of visualization. Would it be interesting, for example, to show just the journals that had contributions from a majority of the poets involved? Might this reveal some of the underlying groupings in the poetic field once we compared it with poets involved in another modernist journal from the period? Could we add a temporal dimension by displaying only those journals that were in publication during some smaller unit of time (e.g., one year)? What would the graph look like if we set 「学校」 at the center, set the poets at the next level up, and then had the rest of the journals form an outer ring or a line at the top? Might this give a better sense for how weakly or strongly connected these poets were in relation to other journals? These are some of the things I would like to continue to work on next week. I think I will also return to the UCINET program to see if I can extract the poet-to-poet and journal-to-journal graphs that will hopefully prove most conducive to meaningful network analysis (i.e., measuring for betweeness, centrality, etc.)

My apologies for the technical and overly detailed nature of these posts. They do not excite in the way that meta-level analysis hopefully will, but it's only by slogging through the mud that we can reach the other shore. 

Back to Work

After a long hiatus, I've finally been able to find time to get back into my SNA work. I completed my preliminary data entry last month, which involved inputting information for all poets affiliated with the poetry journal "Gakko" and the number of contributions each made to modernist poetry journals between 1920 and 1944. Today, my primary goal was to input the data into some SNA analysis tools and see if I could produce a two-mode graph in which links are weighted according to number of contributions made to a particular journal. I was able to do this quite easily in ORA, which then allowed me to produce a predictably messy graph. But what I was really keen to try out was to load the weighted data into UCINET so as to pull apart the affiliation network and see how the poets are connected to one another through the journals. This proved more difficult than I had thought, as ORA couldn't output to UCINET format. Without this step, I will likely have to input the weights manually in UCINET and go from there.

Beyond such technical details, the broader problem that I need to begin addressing is what I'm going to be able to do at the analytical stage that will reveal anything interesting. Part of the problem is learning what sort of analytical algorithms are possible and sensible given the structure of the underlying data. The other part of the problem is coming up with the right questions to ask about the data. Is it centrality measures that I am most interested in? Am I looking for clusters within the network? Do I want to create a kind of network DNA fingerprint for each poet to see how the participation of each does or does not align with others? I guess what I need to really think about are the questions that can't be answered when one has just individual data. Or even if the results do point to realities that would seem obvious to anyone familiar with the poet, the point is to look at the results in aggregate and consider what they might be able to tell us about the modern field of poetic production seen from a broader scale.  

Getting Started

My first project is to take some of the lessons from social network analysis and see what they yield when applied to literary networks. As my object of analysis, I've decided to use the dataset compiled in 『現代詩1920-1944ーモダニズム詩誌作品要覧』. It provides a record of every poem or article published in 166 different magazines (2,695 volumes in total) between 1920 and 1944, and includes 103,485 works by 4,171 different authors. Owing to the large amount of material and the necessary time it would take to do all of the data entry myself, I've decided to begin with a small subset of poets and trace the networks by which they are linked. It is also hoped that even with a small fraction of poets represented, I might be able to build the foundation of a morophological index to the ways that poets participated in the culture of modern poetry journals. Data from the above volume will also be combined with biographical data to see what kinds of correspondences emerge across different kinds of connections (education, birthplace, literary style).

To begin with, I've decided to work with the subset of poets who contributed to 「学校」(gakkō), a regional poetry magazine started by Kusano Shinpei in 1928. It was a short-lived magazine (printed using the mimeograph) whose contributors consisted of both local poets with ties to the Fukushima region and metropolitan poets already well established in poetry circles. My reasons for starting with this magazine have to do with its small size, its regional locus, and a familiarity with the material. If the initial results turn out to be promising, I will repeat what I'm doing here with a journal of similar size (perhaps a small-time metropolitan publication).

The first step is to devise an effective and efficient method for moving the data from its current form into something that I can manipulate as network data. This means creating a database in which I can store and easily access the relevant information. Until I have some time to teach myself about database design, however, I've chosen to work in Excel to create a simple spreadsheet listing names (with unique IDs), birth dates, birthplace, education, poetry journals contributed to (with unique IDs), and number of poems or essays contributed to each journal. Inputting this information for each of the 25 poets who contributed to Gakkō, while time consuming, will be the easy part.

Having input information for just a third of the poets at this point, a couple of questions and ideas have already come up as to what problems I might encounter at the analysis stage:

1. Does the short life-span of many of these magazines present a problem in terms of capturing social network diversity at the synchronic and diachronic levels? In other words, might we have a situation in which poets moved rapidly through different magazines, resulting in rather simple network formations at any one point in time?

2. This is related to the first point. Is there an effective way to display the life-spans of each magazine alongside the network data? We will need to create some sort of chronological chart to do this.

3. What do we do with those magazines that may have had only a couple of issues? Should we simply reject them as isolates?

4. There is inevitably going to be a certain amount of abstraction taking place here, and one wonders what we lose by giving equal value (i.e., one point) to every contribution. Does a short two-line poem equal the same as a long-verse narrative poem spanning several pages? And what about contributions that appear in the same issue? Should they have equal value?

 

First Steps

This blog has been created with two simple purposes in mind. First, to keep a record of my missteps and small successes as I pursue projects under the rubric of digital humanities 2.0. Second, to serve as a space to introduce and reflect on some of the ways that our appreciation of literature and literary history might benefit from the careful (and always tentative) application of quantitative methods. My specialization in modern Japanese literature will naturally skew these objectives toward certain kinds of content, but my hope is that the methodologies on display here will be of general interest to those in other fields as well.