This post is part of a series of blog posts published in 2015 on digital scholarship and digital humanities. Some information may be outdated. Questions? Please reach out to us online or at the Information Desk.
This third and final blog post in the digital scholarship series focuses on a couple of free and relatively simple digital tools, Voyant, used for word analysis, and TimeMapper, used for making maps and timelines. The intent is to demonstrate how such tools might be useful for class assignments and smaller digital projects. LMU student Domenic Olmeda ’16, who worked for the Digital Library Program this summer, was asked to experiment with them. Much of the following post features his reflection on this experience. (Thank you, Domenic!) As an English major, he chose to use Voyant and TimeMapper to explore Joseph Conrad’s Heart of Darkness. They can of course be applied to many other academic subjects and topics.
Word analysis tools like Voyant are not simply for counting words or identifying the location of words within a text. They generate visualized quantitative data that, among other things, inspire new inquiries, help support scholarly arguments and enable scholars to examine large corpuses. During Domenic’s brief experimentation with Voyant he was able to literally see Heart of Darkness grow darker through Conrad’s word choices. He explains:
The image of darkness plays a pivotal role within the novella as Conrad uses depictions of darkness, shadow, and gloom to represent the wickedness and depravity into which Marlow, the protagonist, descends. The text can be read as a chronicle of Marlow’s journey from a land of familiarity and peace to a place of darkness and despair. As you can see (below), “darkness,” which appears 25 times, shows up most frequently at the end.
(These Voyant graphs show the frequency of the word “darkness” and the words “black” and “white” in Heart of Darkness. You are welcome to see and play with this Voyant session.)
By looking at words like “black” and “white,” Domenic was also able to see a looming darkness at the beginning and the prevalence of darkness at the end (see above). According to Domenic, the tool did not so much teach him something new as it, through visualization, gave him a better understanding of the text’s structure and how that structure exemplifies its themes.
Word analysis tools are used for examining all kinds of texts, not just literary ones. Take a look at these Voyant visualization of MSNBC headlines and Fox News headlines from January-June 2015, content that Domenic so kindly gathered for us using the Internet Archive’s Wayback Machine. The visualizations, also known as word clouds, help reveal the divergent tones and rhetoric of the two partisan networks. Of course, to really understand and make meaning out of these word clouds, one needs to explore the results further and look to outside sources for context.
(Two slides from Domenic’s TimeMap)
Domenic found TimeMapper to be more involved and, appropriately enough, time consuming (view his TimeMap). He had to conduct research, decide how to divide the information up between slides, choose the images and, of course, he had to write the content. Then there was the revision process. Domenic describes the experience best:
I am well versed in Joseph Conrad’s Heart of Darkness. I’ve read it about five times. I’ve given PowerPoint presentations on its historical impact, and I’ve written term papers on its literary significance. Despite this I realized that there is still much more to learn about the text after using TimeMapper.
For my TimeMapper project, I analyzed Heart of Darkness’s narrative with its historical context by plotting Marlow’s journey alongside the development of the Congo Free State. What resulted was a vivid picture of just how closely Conrad’s narrative followed the Congo’s history. Through the use of TimeMapper, I was able to see how the atrocities committed by King Leopold’s administration were reflected in Conrad’s novella.
Additionally, TimeMapper did more than affect how I read Heart of Darkness. It forced me to pay close attention to the way I present my research. Being an English major, I initially wanted to fill my slides with lofty paragraphs and flowery language. However, I soon realized that my slides were way too long and difficult to read. My approach was working against what TimeMapper was designed for. In addition, I was asked to write for a general audience, which meant I had to change the way I write. So, I cut down the information, split up my slides, edited my word choices, and broke the timeline down into more digestible sections. As a result, not only did my understanding of Conrad’s novella improve with this project, but also my skills as a writer.
The above are just a few examples of how these tools might be used, and there are plenty of other relatively simple and free tools out there to explore. For example, this fall Professor Jennifer Ramos (Political Science) and I are experimenting with TimelineJS. Students will be using it to illustrate shifts in international policy over time. Her students will also be using Google MyMaps and Storify to map and track news events. Last semester Professor Holli Levitsky’s Literature of the Holocaust class (English/Jewish Studies 398) created digital projects in Tumblr. And then there is Professor Dermot Ryan’s (English) Digital Eighteenth Century class that used a variety of tools.
If you would like to learn more about incorporating digital tools into class assignments please visit the Library’s DS libguide and ds.lmu.edu to learn more about digital scholarship and digital humanities.
To learn more about Voyant, I recommend watching Dr. Tom Liam Lynch’s “Voyant Tools Tutorial.” It focuses on English literature but it’s helpful for gaining an understanding of word analysis tools in general.