Posts Tagged visualization

Constellations at the Convention: 10 Years of MLA Data

Title slide with a tree against star trails with caption 'Constellations at the Convention: 10 Years of MLA Daya'

Yesterday I had the chance to speak on a panel about “The MLA and Its Data: Remix, Reuse, and Research,” which I organized on behalf of the MLA’s Committee on Information Technology. The panel was very successful, due largely to fabulous co-panelists: David Laurence, Ernesto Priego, Chris Zarate, and Lisa Rhody. Ernesto has shared his slides for his presentation on his and Chris’s analysis of tweets from last year’s convention. Unfortunately we missed Jonathan Goodwin, who became ill. Lucky for us, he shared his talk as well.

What follows is the text of my talk, “Constellations at the Convention.” The metaphor of the title suggested itself immediately as I began looking at the network within Gephi, but I couldn’t help but think of Matt Kirschenbaum’s post following the 2011 MLA Convention, “The (DH) Stars Come Out in LA.” I think that the methods I’ve been able to begin deploying here might help us track the star system—if not within the profession, but within the convention.

Even though I say it within the talk, it’s critical that I acknowledge up front the assistance of two people. First, Chris Zarate kindly provided the data from the MLA that I asked for. (The MLA itself needs to be thanked for being willing to support this scholarship.) He made suggestions about the sorts of information he could provide me and gave me exactly what I asked for. Unfortunately, since I had never done something like this before, I didn’t quite know what to ask for. So when I discovered the data weren’t quite as I needed them, my colleague Sara Palmer who took the raw XML and transformed it with XSLT and Python into a format that I could use. Sara and I then spent several hours playing with the data and then talking about the different things that we were seeing. She identified the Midwestern Mafia as a question worth pursuing. Finally, Rebecca Sutton Koeser pointed out the Javascript exporter plugin for Gephi, which is why you can now play with the data easily.

I appreciated the interest from the crowd and the thoughtful questions about “algorithmic cruelty” and where such work might lead in the future. If you want to play with the data yourself, you can download the Gephi file of the 2014 and 2015 Mark Sample data. I will see what I can do about sharing the MLA data set. But for the moment, you can explore the four different networks that I showed.

As always, my work is Creative Commons-licensed. Let me know what you think!

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Mapping some Familiar Mark Z. Danielewski Tweets

A few days ago, I stumbled across a Twitter conversation about House of Leaves. That’s generally enough to get my attention. The people involved were an added enticement. But the conversation among Jesse Stommel, Chuck Rybak, Sean Michael Morris, and Paul Benzon took a different direction when Paul asked, if anyone had “theories on what’s up with the MZD numerical tweets?

This was the first that I had heard anything about this, so I quickly checked out Mark Z. Danielewski’s tweet stream. And it was very quickly apparent what Paul was talking about. MZD’s last 8 tweets have been a string of numbers. When I looked at them, my immediate thought was that they had to be linked to The Familiar, his 27-volume serial novel that should start being published in 2014. My second thought was that these numbers looked suspiciously like latitude and longitude.

I had a little bit of time that morning, so I quickly ducked into Google Maps to see what I could find out. The first of his numerical tweets appeared on 17 January 2013: 48-371204-9-7265. I decided to replace the dashes with commas and periods, and entered these coordinates: 48.371204,9.7265. A spot in the forest southwest of Schelklingen, Germany was the result. Easy enough. The second site was in Alles-sur-Dordogne, France.

The fourth tweet was a little more complicated, as it presented an em-dash instead of a dash in the middle of the tweet: 63-84823—20-8712. I decided that the em-dash was most likely a way of signaling a negative value for the longitude, and tried 63.84823,-20.8712. That seemed to work, placing me in Iceland; but to be sure, I removed the negative value, and found the spot in the ocean off Sweden. The sixth tweet contained a similar em-dash, and similarly dropped me in the ocean when I removed the negative. The same thing happened with the most recent tweet, which featured a negative sign at the front of the longitude.

So here are all eight locations:


View MZD Tweets mapped in a larger map

The locations are rather diverse, although only on three out of seven continents thus far. I suspect that we’ll see more places mapped soon. MZD has been tweeting once every two weeks, so I think in another 10 days or so I’ll be adding another location to this map.

It’s certainly possible that I’m completely wrong about these numbers being spatial coordinates. And they don’t begin to explain why he is tweeting a blank, black image along with every set of numbers. But if I’m wrong, I’ll be in good company. Someone blogging at schinjislist.blogspot.com had noticed the tweets before I did and had come to the same conclusion about them being best understood in relation to a map. There is, naturally, a post on the MZD forums, on the subject as well. Update: And, it turns out, some steganographic analysis that has been done on Reddit. 10 points to Paul for finding that as well.

It’s worth looking around the locations. Zach Whalen noticed, for example, that there seem to be several loops or circles near each point. That would work well with some of MZD’s thematics. But again, allways, and allready one must be wary of apophenia.

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