Matt and Steve asked for requests for readings, and said in class that it’s time to get those in! I guess I was waiting for someone else to start a thread that I could chime in on, but maybe I’ll take a break from watching the anxiety show and should start that thread myself.
I’d like to have a little more about network analysis — we had a lot of readings about visualization, and some of those did touch on network analysis, like Klein’s piece on the images of absence, with its extremely elegant arc diagrams, but there wasn’t a lot. I don’t know what the foundational pieces on network analysis are, although I was really intrigued by Lisa Rhody’s work when I saw her in a panel last month.
If we can just add pieces that we really like, I thought Data & Society’s report, “Alternative Influence: Broadcasting the Reactionary Right on YouTube” is very interesting from a network analysis point of view but also fits in with the unit on race and inequality and algorithms. Anyway I’m rather selfishly interested to know what other people in the class think of it.
Hi Nancy & everyone:
I’m interested in reading this together at least as recommended reading:
Chapter 9. “Wear and Care: Feminisms at a Long Maker Table,” by Jacque Wernimont (Arizona State University) and Elizabeth Losh (College of William and Mary) open access
With the rise of popularity in hacker/makerspaces has come an old reproduction of inequality at the sites of innovation and education in which women, people of color, middle-aged and elderly citizens, queer and genderqueer people, and people with disabilities are affectively and/or economically excluded. This chapter leverages pedagogical case studies, including our summer course, Feminist Digital Humanities: Theoretical, Social, and Material Engagements around Making and Breaking Computational Media, to sketch out a vision of a “long maker table” that draws on the feminist performance art tradition to break into and break open makerspaces that have been traditionally coded as white, affluent, masculine spaces.
Open access here: https://scholarworks.wm.edu/asbookchapters/5/
Thank you.
Also,
I’m interested in reading this (by Lauren Klein) together as well.
Chapter 44. “Timescape and Memory: Visualizing Big Data at the 9/11 Memorial Museum,” by Lauren F. Klein (Georgia Institute of Technology) open access
This chapter positions Timescape (Local Projects, 2014), a large-scale data visualization installed in the 9/11 Memorial Museum, as evidence of how humanistic inquiry must stand alongside data visualization and other computational practices if we are to most fully address the complexity of twenty-first-century daily life. I demonstrate how Timescape, and all data visualizations, must be analyzed on three levels: 1) at the level of the data-image, 2) at the level of data-processing, and 3) at the level of the dataset itself. By analyzing Timescape according to this scheme, I show how the piece must be interpreted so as to better understand the assumptions and arguments embedded in its design. I claim that the knowledge produced by data visualization is always partial, and that no quantity of data, however large, and however it might be visualized, can be made to represent the global impact of 9/11 in a single view. I conclude that Timescape, as a result of its relation to 9/11 as a media event, does not merely produce knowledge in the particular terms that its algorithms identify and visualize; it also represents the larger process of knowledge production itself.
Open access here: https://smartech.gatech.edu/handle/1853/59435
Thanks again.