Tag Archives: Voyant

Mapping Dubliners – Two Gallants

For my Digital Humanities final project, I wanted to work with a text of a literary classic to see how DH can interpret, re-visualize, or present a new perspective about a book that has been analyzed by many scholars. Dubliners  by James Joyce was an easy choice since it takes the reader to a multitude of locations within the stories told. In Joyce’s words: “My intention was to write a chapter of the moral history of my country and I chose Dublin for the scene because that city seemed to me the centre of paralysis. ” (Letters, vol. 2,134)

Dubliners is a collection of 15 stories that depict a variety of characters as Joyce paints their portraits of life in the Irish capital. He focuses on both children and adults of the middle class: housemaids, shop girls, clerks, teachers, students, swindlers, and businessmen. Through these moments of experiences, Joyce holds up  a mirror for the Irish to observe and study themselves. Joyce’s stories not only allow us to peek into the homes, but also reveal the hearts and minds of these Irish whose lives as they intermingle through the space of Dublin reflect its spirit. The subtle social and cultural connections create a sense of shared experience and evoke a map of Dublin and its life. The story of “Two Gallants” from Dubliners provides the most locations in the entire book, so I started there.


I began by reading  the digital copy of Dubliners available in Project Gutenberg and marked the locations mentioned in the story of “Two Gallants” using Diigo, which allowed me to save a list of locations.







I have uploaded the story into Voyant to see the text around the street names. Also I was interested in the various association of characters to places and spoken or narrated words.

Viewing the Cirrus function, it became evident that Corley and Lenehan, the two characters wondering around the streets of Dublin are of the utmost importance of the story. These two names have topped the list of words most frequently appearing.


Next, I have explored Voyant’s “Links” tool to examine the connections of the two main characters and their actions or the most common words linked to their names as a way to conjure meaning.

I was interested in further looking at Corley, since his name came up the most – 46 times. The “Bubblelines” function provided me with a linear graph of the name’s frequency, which is more applicable when we think of how stories are told in a similar fashion. The “Trends Graph” gave another view of Corley’s appearance in the story.

Using an Excel spread sheet, I have assembled the dataset including names of characters, locations (the story names streets, squares, lawns, colleges), longitude and latitude of those locations, and added the action or dialogue taking place.  The coordinates finder site allowed me to search up those numbers, which after I organized and listed in Excel was able to upload into CartoDB and Palladio.

CartoDb’s wizard function in the Map View allows the dataset to visualize over the map of Dublin showing the locations mentioned in “Two Gallants.”

The Cluster function of CartoDB shows the actual locations on the map of Dublin. By hovering over the points, the name of the character and the action that had taken place at that location in the story will appear.

CartoDB Heat map gives a progressive look at the movement of the characters in the story. It is projected over a night map of Dublin,
which makes it visually more relevant since the story takes place at night.

Analysis: this project shows the very beginning of how DH might explore literary texts with a variety of purposes. My project ends here with questions and possibilities for further steps:

  • How to continue?
  • What can be gained?
  • Who might be interested?
  • What more can we learn about the characters?
  • How have these locations changed?
  • Should the project expand to link photographs of the locations?
  • Should the information include what sorts of activities happen in those areas of Dublin today? Do they differ from the activities during Joyce’s time?
  • Would crowdsourcing be a useful contribution to the project?
  • As a different approach or addition to the project, a twenty-first century Dublin could be constructed and linked to Joyce’s Dublin as it appeared in 1914.

Other Projects on Mapping Dubliners

Compare Tools: Voyant, CartoDB, Palladio

The opportunities created by new web-based free open source technologies in Humanities have been significant in re-examining, interpreting, and relating information from literary, cultural, social, political, or historical data. As we worked with the Library of Congress’ SWA Slave Narratives dataset, it was a journey to discover the variety of ways to visualize the intricate elements and connections within by using three of the visualization tools.


Voyant is a text mining tool that manipulates text through a range of analysis, such as cirrus, graphs, context, and verbal patterns reveal determining elements of the given data. To approach text through word count or patterns is to break it down to a level that we could not accomplish easily on our own. I feel that this tool brings out the other human side of text that reveal words and meaning through numbers.


CartoDB sets humanists off on a different journey. It pulls the data from the set and spreads it out on a map. It layers information and over laps the data to show a geographic relevance in the text. The geography of the interviews in the slave narratives provided a new narrative that grew out of the reality of the locations.


Palladio seemed the easiest to work with as far as the interface concerned. It provides a map of such informational detail that is probably the most difficult to gather by hand. It is an excellent tool to analyze relationships between people, locations, events, and ideas. These connections are illuminating relationships that have the possibility to create a new world of understanding about something we thought we knew. For instance, Palladio paints a busy visual of the relationships in the Jazz World, manages to make sense of the communication around The Letters of the Republic, and gives layers of insight into the slave narratives.

In comparing these three digital tools, in light of the slave narratives, I’d prefer to use Palladio. It seems that the network analysis of those narratives provides a deeper insight. However, there is no reason not use all three and compare the results and the questions each tool was able to bring up or answer. Although the nature of the project and the type of text/dataset and desired results may narrow the tools down to text mining or mapping there is no reason not use them interchangeably. Overall, these tools are able do something we humans would or could not easily produce, thus the possibilities are endless.