Thanksgiving by the Numbers

Today, our blog post is brought to you by the staff of DASIL, including our peer mentors, programmers, and our Iowa History Project team. Enjoy some food for thought as you digest your Thanksgiving meal.

Thanksgiving Word Cloud

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Access to Research Includes Access to Data!

In February 2013, the Director of the White House Office of Science and Technology Policy (OSTP) issued a memorandum to all agency and department heads entitled, “Increasing Access to the Results of Federally Funded Scientific Research”.

The memo directed federal agencies that award more than $100 million in research grants to develop plans for increasing public access to peer-reviewed scientific publications. It also requires researchers to better account for and manage the digital data resulting from their federally funded research. (At the same time, the OSTP directive acknowledges that access to some data needs to be controlled to protect human privacy, confidentiality of business secrets, intellectual property interests, and other reasons.)

The OSTP recognizes that research data are valuable and need to be preserved. Increased public access to data – along with better access to the published literature – is fundamental to research, and permits

  • more thorough critiques of theories and interpretations, including replication of research results,
  • scholarly innovation that builds on past work, and
  • practical application of scholarly discoveries.

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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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Geovisualizing the Ebola Crisis

Media coverage of the Ebola virus outbreak has thus far represented a geospatial and cartographic moment.  Mapping of the outbreak and geovisualization of its different facets is doing much to frame public understanding of the crisis as well as the policies that are attempting to address it.

Population flow measured by mobile phones from Worldpop.org.uk/Flowminder

One the one hand, the widespread use of geovisualizations to report on the Ebola epidemic reflects the high density of information that maps provide.  This has only been increased by the swift integration of traditional cartography with animated graphics and other web-based media to create ever more visually appealing infographics that have a geographic twist.

Geovisualizations demonstrate the importance of place and scale—two fundamental aspects of geography—to the Ebola epidemic.  Maps of the worldwide locations of where infected patients are staying, the locations of medical centers equipped to handle Ebola are located, not to mention the geographic concentrations of new cases give readers a place-based sense of either unease or hope.  Maps of Ebola-related travel restrictions tell us how national governments are responding to the ongoing risk of spread.

But West Africa remains the epicenter of this Ebola outbreak and the region is already suffering a tremendous human and economic toll from the virus.  Using geospatial approaches to understand patterns of human mobility will is playing a central role in efforts to prevent the outbreak from reaching even greater proportions.  One of the best examples of this is work done by researchers associated with the Flowminder Foundation which reveals at an unprecedented level of detail the movements of people in and around the parts of West Africa with the highest concentrations of Ebola cases.  What made this work possible was the use of cell phone records, which are proprietary to the providing telecom companies and sensitive information for the phone users themselves.  Given the growing need for this type of spatial epidemiology to address fast breaking and complex emergencies like the Ebola outbreak, we can expect that norms around data availability and use to change quickly and in unexpected ways.


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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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