8A Thinking Through Networks I (31 October)
At this point of the term after our textual data storytelling exercise, we will move to more abstract representations of data. Again, you might go to www.lynda.com and watch some of their materials on data visualization. We also need to refresh our memories about classificatory systems from week 2 and our collective project. We will begin with perhaps one of the most unexpected applications of networks: to narrative.
Reading before class: Moretti “Network Theory, Plot Analysis;” Weingart “Demystifying Networks,” Meeks/Krishnan “An Interactive Introduction to Networks;” excerpts from Galloway/Thacker “Nodes/Edges” The Exploit.
Explore before class: Choose two of the DH projects below and explore them, taking notes to present in class. What does each network represent? What kinds of relationships do they show? What parts of the world do they analyze? What is the critical language they use to describe their research inquiries? Network graphs are said to be made up of nodes and edges. How can those concepts be applied in the context of the humanities? How do various projects work to “unflatten” their visualizations?
Manifest / Viral texts project / Mapping the Republic of Letters / Orbis / Stylometry and Medieval French literature / Networks of Book Makers / Ibadi Scholars in the Maghreb / Kindred Britain / Hestia / World Literature / Shakeospeare / New Maps for the Lettered City
8B Network graph Lab (2 November)
Many network and data visualization environments exist out there. We will experiment with some of them in lab today. We will be trying Palladio and NodeGoat. What do these different graph visualization systems purport to do? What kinds of data are required to make them work? What is the relationship between a map and a network? How are data structured for different network platforms?
We try different datasets provided by the instructor: Literary Geographies of Christine de Pizan, the Exploring Place in the French of Italy and our group spatial project data and others (like this one for the US presidents). Our class exercise will be creating a network visualization of the Wikipedia page for Cinema of Egypt and for List of Egyptian films using NodeGoat. A useful FAQ for Nodegoat can be found here. A series for Youtube videos for how it works can be found here. Other useful lists at IMDB are here and here.
Keeping in mind Drucker’s idea that no data has an inherent visual quality, how do the assumptions of the platforms change what we see? What kinds of challenges do we have when sharing and reusing network graphs created in the cloud? What kinds of data have been captured (or computed) to allow such complex networks to be visualized? What are some places in the humanities we might push forward to study networks? What kinds of networks could be studied in the Arab world from recent big data initiatives? What are some possible concepts of the node? Of the edge?
Blog post #5: What did you learn from the NodeGoat exercise about modeling a set of relationships in a network (finish this after class on Monday 9 Nov)?