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Z-Axis Tool Updates

* As we continue to develop the z-axis tool, we would first like to extend our appreciation to the 2015 Modernist Studies Association “Z-Axis” seminar participants for testing and providing valuable feedback for an early version of the tool. We would also like acknowledge and thank Emory University’s Center for Digital Scholarship. Much of our current and future development of the tool follows on a demonstration of the tool at and feedback from the Center.

Z-Axis: From Methodology to Useable Tool

How does a text shape a city? How does a novel contest or reify popular narratives of a given place? How does the history of a place inform our understanding of a text? Such are the questions the Modernist Versions Project sought to explore when it developed the z-axis methodology—a methodology that produced a three-dimensional model that visualized the way a text transformed a city.

An image of our original workflow
An image of our original workflow

The first instantiation of the project requiredheavy XML markup and knowledge of XSLT by already time-stretched researchers. The time spent encoding, however, truncated the time literary scholars had to do what they do best: analyze text. If we wanted to develop a methodology that scholars would use, we would have to make it accessible. We needed to reduce the barriers of time and computational expertise usually required for geospatial analyses of modernist texts. We needed to develop a tool that was easy to use and allowed researchers to upload the texts and maps that interested them.

And we did.


Project Updates

The past several months have seen some substantial updates for the z-axis team. First, we’ve turned a time consuming methodology into an easy to use, working tool:

The website for the z-axis tool
The website for the z-axis tool

Early versions of the tool allowed users to choose from a small repository of texts or upload their own text to the server. The tool then used the Stanford Core Named Entity Recognition software (NER) to pick out all the place names and identify their frequency. The z-axis tool mapped the place names and warped one of three listed maps based on the frequency of place name occurrence in a text.

An image of an early z-axis map
An image of an early z-axis map

Developing the initial tool was the first major step forward for the team. The second step forward was user-testing. The Z-Axis Seminar at the Modernist Studies Association conference in November 2015 gave us our first chance to test the tool with our target users: modernist scholars. The participants used the tool to analyze a modernist text and wrote papers based on their geospatial readings of Mrs. Dalloway, Jacob’s Room, The Secret Agent, and other modernist works. Their intricate analyses of these texts showed us that the tool was in fact useful for literary scholars; it also proved to us that we (or rather our brilliant developer, Colin Jones) could design the tool to do so much more.

New Features

The new features of the z-axis tool are inspired by the suggestions of the MSA workshop participants and feedback from Emory University’s Center for Digital Scholarship.

Users can now

  • geolocate and map sentiment present in a text,
  • upload and georeference their own maps of London,
  • capture images of their warped maps, and
  • isolate sections of a text to map.

We’ve also

  • expanded our repository of warpable maps,
  • expanded our list of comparative maps,
  • added a feature that allows users to upload maps,
  • added georeferencing capabilities for user uploaded maps, and
  • added floating tags over the map that identify the place names associated with a warped area.
Z-axis map with sentiment analysis
Z-axis map with sentiment analysis

The development we are most excited about is sentiment analysis. This added feature means that you can see how a text like Mrs Dalloway inflects London with positive or negative sentiment. Is Hyde Park associated with positive language? How does this compare to the area around Big Ben? Are there distinct clusters of positivity? Why?

Your Feedback

As we continue to develop the z-axis tool, we plan on refining the sentiment analysis to identify more nuanced emotions such as happiness, sadness, anger, and frustration. We will also add a feature that shows you which section of the text is linked to a particular place. Because this is a tool designed for researchers, we welcome your feedback. Let us know what would you like to see from this humanities centered, geospatial analysis tool.


Katie Tanigawa is a Ph.D. student in English at the University of Victoria and Research Assistant with the Modernist Versions Project. Check out more of Katie's work at

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