20% of course grade
Due: Friday, March 13 by 10:00 pm to Blackboard
Extended Office Hours:
Monday, March 9: 1:15 – 4:15 pm
Tuesday, March 10 (half of class)
Thursday, March 12 (whole class)
Since our first assignment in this class, we’ve been discussing data in relation to literature by exploring the digital humanities, as well as reading a novel that seems to call for a particularly “data-based” approach to reading. Your second assignment therefore asks you to experiment with computational methods of literary analysis, using one or more tools or applications to perform a “machine-assisted” reading of Mark Z. Danielewski’s Only Revolutions. You will then write a reflective analysis of your results and of the process itself.
This assignment has three steps:
- Use the computational tool(s)/method(s) of your choice to analyze _Only Revolutions _and to visualize the results of that analysis in some way.
Analyzing Only Revolutions
Just as if you were writing a more traditional literary analysis, or close reading, of Only Revolutions, you are free to choose_ _what aspect(s) of the novel you want to analyze. Perhaps you want to see where particular words appear and how many times they appear; perhaps you want to explore what words Sam and Hailey say; perhaps you want to investigate the dates used in the chronology sidebar further. In deciding how to proceed with your analysis, you may need to experiment with a variety of different tools and approaches before deciding on a specific path to pursue. However you choose to analyze the novel, you should think about what interpretations of the novel your specific method of computational analysis makes possible (or perhaps easier, or different). What interpretations does analyzing the novel in this way enable?
Visualizing the results
You also need to think about how you want to visualize the results of your analysis. What’s the best — and keep in mind that “best” can mean any number of things depending on the results of your particular analysis and the goals of your particular project — way to visually communicate these results and why? Keep in mind, also, that this visualization(s) can be more of a “proof-of-concept” than a finished product. Perhaps your vision exceeds your current technical abilities/the constraints of this particular assignment. You should feel free to submit a speculative prototype of this vision created using a program like Photoshop or InDesign (or an analog visualization you draw by hand).
Listed below are some tools you could use for this project, organized by type of tool and including some indication of their general ease of use:
Text Analysis Tools
- Dipity (easy)
- ManyEyes (easy)
- Mondrian (easy to medium)
- Timeline.js (easy to medium)
- Cytoscape (medium)
- Gephi (medium to hard)
- Great tools for data visualization
- Alan Liu’s DH Toy Chest
- The Rhetoric of Text Analysis: Tools
- TAPoR recipes for text analysis
- _Only Revolutions _reading tools: Hayles’s Only Revolutions Commentary; VizOR
- Getting started with Antconc: http://hfroehli.ch/workshops/getting-started-with-antconc/
- Corpus Linguistics for Historians: http://historyinthecity.blogspot.com/2013/12/corpus-linguistics-for-historians.html
- How Did They Make That?: http://dhbasecamp.humanities.ucla.edu/bootcamp/2013/08/28/how-did-they-make-that/
- Introduction to Network Visualization with GEPHI: http://www.martingrandjean.ch/introduction-to-network-visualization-gephi/
- There are MANY more tutorials listed on Alan Liu’s DH Tutorials page
Of course, if you are familiar with particular programming/scripting languages, libraries or toolkits that may work for this task (Processing, R, Python, D3, Prefuse, etc.), you should feel free to use them.
- Write a 3-4 page (double spaced, 1” margins, 12 pt font; 800-1300 words) reflective analysis of your results and your visualization(s). This analysis should be informed by the conceptual and theoretical issues connected to the digital humanities and/or data visualization that we have discussed in class, and it should incorporate at least one of the non-literary texts we have read since February 10 (this includes recommended readings).
Here are some questions you might consider for this portion of the assignment:
- What new or different perspective(s) on Only Revolutions does your machine reading provide? What interpretations does it make possible that traditional methods or modes of literary analysis might not? What are the advantages and disadvantages of adopting what we might call a computational perspective on a literary text?
- How can traditional modes and methods of literary analysis be supported by machine reading? How can they be mutually productive?
- In what sense do text analysis and/or data visualization ask us to reconsider our governing assumptions about what a text is, what is involved in “proper” reading, and what knowledge production looks like?
- Is your visualization(s) a representation or an abstraction of your data and/or your interpretation of the novel? Or something else? What is the difference between these modes, and how does this difference apply to your project?
- Is your visualization(s) interactive? Why did you make that choice? What does interaction contribute? How does a lack of interaction affect the visualization(s)?
- Did you experience failure while working on this project? How so? Is this failure productive in any sense? Does it tell us anything about machine reading, about traditional methods of literary analysis, and/or about knowledge production?
This is not an exhaustive list of questions and topics. As always, these questions are intended to get you started thinking, not to do your thinking for you. You are free to write about what specific aspects of your results and their implications interest you most. Your paper should be focused, specific, and it should integrate examples with analysis. The point of this portion of the assignment is for you to think through the affordances and constraints of the machine reading and/or visualization itself, and what some possible implications of these affordances and constraints are. Please be sophisticated, creative, and focused.
- Post your data visualization(s) on our course site (or provide a link if it is hosted somewhere else; categorize your post under “Machine Reading”), along with a brief description of your method(s), your results, and the design choices you made in creating your visualization(s) (500-600 words total). Why have you chosen to present your data in this particular way? What conscious stylistic decisions did you make? What are you trying to accomplish with your visualization(s)?
As always, please come talk to me if this project seems daunting, or if you’re not sure where to start.
Examples of Similar Projects
- Cyrus Mulready’s “Close/Distant Reading Assignment.” Reading through the process Mulready assigned to his students may help you devise your own methodology for analyzing OR.
- Projects by students in Brian Croxall’s Digital Humanities class at Emory in 2011. See some examples of student work on a similar assignment.
- Reflections on “machine reading” as a methodology from students in Rita Raley’s classes (read the comments): https://engl146.wordpress.com/machine-reading/; https://engl252.wordpress.com/machine-reading/
- Examples from students who did a similar project in Roger Whitson’s class.