Data Across the Curriculum: Qualitative Literary Analysis in the Humanities

This semester, students in Professors James Lee and Erik Simpson’s special topic seminar, “Milton, Blake, and Frankenstein,” will use NVivo, a software for qualitative literary analysis, to create word trees visualizing the use of the word “sublime” in Milton’s work. This is an outgrowth of teaching that Lee began in 2013 when, as DASIL’s first Faculty Fellow, he designed a seminar on Shakespeare and Renaissance literature that used NVivo to investigate first the corpus of Shakespeare’s work and then over 20,000 documents from the Early English Books Online (You can see previous DASIL blog posts written by Prof. Lee about this research here and here).

Lee’s classes use NVivo to visualize data and generate descriptive statistics about datasets that can be exported to other programs, such as Tableau (another software for data visualization). These programs are particularly useful to students because they provide a user interface, allowing students to manipulate data easily, without having to learn a new programming language.

Lee’s personal research incorporates some of the same methodologies that he teaches to his students in class. His current project, the Global Renaissance Project, is partially funded by a “Digital Bridges for Humanistic Inquiry” grant from the Mellon Foundation. It uses network analysis and topic modeling to examine discourses surrounding race in Renaissance texts. The figure below is a still of the prototype for the topic modeling aspect of the project, which identifies clusters of words with a disproportionately high probability of occurring together in text.

Screen Shot 2016-03-24 at 6.41.14 PM

So far, the project has revealed that Renaissance representations of race were centered on cultural, geographic, and commercial factors; race as a biological or physical concept emerged as a justification for English imperialism after the Renaissance. Lee currently collaborates with professors at the University of Iowa on a “linked reading” project that combines two databases to discover how networks of printers and publishing houses contributed to the Renaissance discourse on race.

For Lee, the biggest challenge presented by the integration of digital analysis into classes is changing his students’ mindsets. He observes that humanities students are often used to classes in which students and professors develop ideas through discussion. In contrast to discussion-based classes, working with the digital humanities can mean that students exert effort in a particular line of inquiry that doesn’t yield any concrete results.

The iterative process of data analysis can be frustrating, especially since students often don’t anticipate undertaking it in their humanities courses. Professor Lee hopes continuing to integrate digital humanities into classes like the seminar he is co-teaching this semester, will help to convert students’ frustration into a “tinkering mentality” so that students come prepared to continually adjust their hypotheses based on their analysis and visualization of the data.

To explore the Global Renaissance Project prototype, click here.

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Map of Majors Declared at Grinnell College from 1985 -2015

Explore the geographic trends associated with declaring a major at Grinnell College!

For the map:

    • The Contents button(contentsbutton) will display all layers. Unclick the checkbox next to the layer name to hide the layer. To view the legend, click on the “Show Legend” icon (contentsbutton) below the layer name.
    • To examine other majors, find the “Change Style” button (contentsbutton) below the layer name you wish to view, then select the desired major from the “Choose an attribute to show” drop-down menu.  You may alter the map with colors, symbols or size.
    • Click on an individual country or US state to see available data on all majors.


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Investigating the Spatial & Temporal Trends of Declaring a Major

The start of the school year is a time many students start putting thought into what disciplines to study for the remainder of their collegiate careers. Many on-campus resources such as the Center for Careers, Life, and Service are already in the full swing of advising students, such as the “Choosing Your Major” info session on Sept 21st from noon to 1 in the Joe Rosenfield Center. Here in DASIL, we thought it would be fun to investigate what Grinnell College students majored in over the years to illustrate the transformation of student academic patterns. Using data from the Office of Academic Affairs, Office of the Registrar, and the Office of Analytic Support and Institutional Research, we created two interactive graphics. One is a line graph presenting the number of declared majors over time from 1991 to 2015 by major and rank compared to other majors. Our second visualization is a geographic map with two layers: the US layer breaks down the proportion of students by state and major from 1985 to 2015, while the world layer illustrates the proportion of international students by country and major.

Click on the Details button below to find out more about the data for each visualization.

For the map:

    • The Contents button(contentsbutton) will display all layers. Unclick the checkbox next to the layer name to hide the layer. To view the legend, click on the “Show Legend” icon (contentsbutton) below the layer name.
    • To examine other majors, find the “Change Style” button (contentsbutton) below the layer name you wish to view, then select the desired major from the “Choose an attribute to show” drop-down menu.  You may alter the map with colors, symbols or size.
    • Click on an individual country or US state to see available data on all majors.

For the line graph:

  • Choose your major(s) of interest in the “Select a major to display” field.
  • Hover over each point to display information on a major’s rank by class year and the number of students declared. Hover over a line to view the path of a major over time.


 

 

The Biology major holds the record for most students declared within this time frame, at 53 students for the Class of 1995. Since its creation, the number of students who major in Biological Chemistry increased leaps and bounds, ranking as the second most-declared major in the Class of 2015, tied with Psychology. Economics shows a general increasing trend over time, while majors like English and Sociology show erratic variability throughout.

American Studies majors appears to be representing the South and Southwest regions of the US, while Sociology is prominent in states located in the Midwest and, similarly, the South. A large proportion of students hailing from California study the hard sciences, especially Biological Chemistry. Surprisingly, there is a significant proportion of biology majors represented in most of the states.

Scoping out, the social sciences and hard sciences are popular disciplines among international students. Economics, Biological Chemistry, and Math are popular, especially in countries like China and India. Several humanities majors are not well-represented by international students, such as Theatre and Gender, Women, & Sexuality Studies.

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A Network Analysis of Shakespeare’s Plays, Part 2: Revising the Social Disorder Hypothesis

In my last post, I described how network visualization represents the beginnings of a method that will allow us to read between the written playtext and the theatrical performance. Its digital method focuses our critical gaze on the exchange between the words and bodies that work together to define Shakespearean performance by transmuting the words of the playtext into character relationships in space. We will compare the network graphs with the language of the playtexts and with still images from performances, to substantiate our claims at three levels of analysis. Using the network visualizations, we aim to address a pressing question in the digital humanities today: can computational methods can teach us something new about literary texts, or do algorithms and visualizations simply confirm readings, arguments, and theories we already know well. The promise of the network method lies precisely in offering to critics a new vantage point that would otherwise not be possible through a conventional reading of the text. The network allows us to rethink one of the oldest stories in Shakespeare criticism and pedagogy, what we will call the social disorder hypothesis. Since A.C. Bradley influentially defined the essence of Shakespearean tragedy as “division of spirit involving conflict and waste,” and not the ultimate reconciliation or renewal suggested by Hegel, generations of critics to the present have described the tragic nature of Hamlet in terms of thanatos: confusion, destruction, and violence that violates natural law, ethics, and social order. Readers of the comedies have developed a parallel hypothesis on social disorder in accounts of the carnivalesque. Drawing inspiration from the work of Mikhail Bakhtin in Rabelais and his World, a long tradition of critics has focused on the inversions and disorderings of political and sexual hierarchies opened up in the chaos of Shakespeare’s comedies. In this story told about Shakespeare, the tragedies and comedies draw their power and enduring interest from the subversive representation of social disorder. For the sake of space, the present argument focuses on Shakespeare’s tragedies, and acknowledges that the comedies and histories require further analysis.

Figure 1

Figure 1. Hamlet, Act 5, Scene 2

This canonical account of Shakespearean drama as a fictional space for the eruption of disorder severing social bonds and overthrowing political hierarchies certainly holds true at the level of plot, and Act 5, Scene 2 of Hamlet is one of the most striking examples of this. However, the critical vocabulary of entropy and chaos – incoherence, conflict, waste, violence, destruction, scattering and disproportion – used describe tragic plot as the unraveling of society and the destruction of human bonds, fails to capture the dramatic technique required in a performance to represent this “scattering” of the social on stage. The network in Figure 1 demonstrates that scenes of a tragic “scattering” disorder and the most disruptive and violent severing of social bonds are precisely the moments where the closest connections between characters are made, and the densest concatenation of network links exists.

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A Network Analysis of Shakespeare’s Plays

What if Hamlet’s “To be or not to be” soliloquy looked like this:

Figure 1 (1)

Rather than like this?

Figure 28

For the past two years, I have been working on ways to do precisely this, by using social network analysis and theory as a way to study literary texts. I’ve examined Shakespeare’s plays to demonstrate how network visualization is a digital humanities method that can “explore” and “negotiate” the space between text and performance in the study of drama, to borrow terms from the Shakespeare critic Robert Weimann. In this approach, digital techniques serve as a way to link traditionally different modes of reading and literary criticism, such as, in the case of Shakespeare, the literary text and theatrical performance. The networks developed in this project use the language of Shakespearean plays to trace the relationships between characters in space, in effect, translating the literary text into a web of spatial relations, which are difficult to perceive solely in the act of reading. The network visualizations map out the connections between every character in all of Shakespeare’s thirty-seven plays at different scales – from the entire play to the individual scene to the line – by counting how much a character speaks (the size of the node), whom they speak to (the edges between the nodes), and how frequently characters interact (the distance between the nodes).

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