Although I came into this class having knowledge of the 1930’s, the skills and resources we have used this semester has allowed me to gain new insight and perspective on the time period and how we can view history overall. Reflecting on what we learned through the use of these digitized tools I am reminded of Tony Guidone’s presentation in which we discussed the benefits and possible downsides to use of these tools. An example of which can be found in Ian Milligan’s article where he talks about the impacts of the Globe and Mail and the Toronto Star being digitized. Before digitization most newspapers were cited around the same amount. However, after the Toronto Star was digitized, it was cited far more frequently than its non-digitized counterparts.1
One of my favorite skills we learned this semester was being able to glitch images and that’s why I decided to use that for my final project. The first time we saw this being used was in Michael J. Kramer’s example of glitching, which places an African American man in the forefront of the image instead of the two other white men revealing a new narrative for folk music.2 I glitched an image of an older man sitting peacefully playing the violin. The glitching process not only created an entirely new feel to the image but allowed me to view details about the image I missed before.
The second tool I used was soundcite to help convey exactly what I was describing. Inserting sound clips makes what I’m talking about seem not only more personal, but real to the reader or listener. As Peggy Seeger suggests, you can’t “live those stories” without hearing the “voices on the recordings, drenched as they were in sorrow, joy, anger, poverty.”3 Without this tool, the reader wouldn’t be able to fully grasp what the meanings behind any of the clips.
The third and final tool I used was the voyant tool which allows me to visualize text in a new way that furthers understanding. It was tricky to use at first, but once I was able to understand the mechanics of it, I was able to begin analyzing different texts. For my project, I compiled various different songs that were popular in the 1930’s and put all of their lyrics into voyant to analyze the songs based on specific words used. Based solely on the songs I chose, I thought that I had an idea of how the text analysis would go, however, after using the voyant tool and taking a look at these songs through a distant reading scale, I was able to notice things I didn’t before. I was initially able to see what words were most commonly used through the use of the “word cloud, with more frequently occurring words shown in a larger size.”4 Some of the popular words weren’t surprising, but there were others I didn’t expect to be on there, which opened up the opportunity to look at these songs and their historical meanings in a completely new way.
Final Project Link: http://jessicadoeshistory.com/cnd/exhibits/show/introductiontomusic
- Milligan, Ian. “Illusionary Order: Online Databases, Optical Character Recognition, and Canadian History, 1997–2010.” The Canadian Historical Review, vol. 94 no. 4, 2013, pp. 540-569. Project MUSE, muse.jhu.edu/article/527016.
- Kramer, and Michael J. “Glitching History: Using Image Deformance to Rethink Agency and Authenticity in the 1960s American Folk Music Revival.” Current Research in Digital History, January 1, 1970. http://crdh.rrchnm.org/essays/v01-08-glitching-history/.
- Seeger, Peggy, Ruth Crawford Seeger, and Charles Louis Seeger. “FOREWORD.” In Sounds of the New Deal: The Federal Music Project in the West, by GOUGH PETER, Xi-Xiv. University of Illinois Press, 2015. www.jstor.org/stable/10.5406/j.ctt130jtfw.3.
- Miriamposner. “Miriamposner/Voyant-Workshop.” GitHub. Accessed November 8, 2019. https://github.com/miriamposner/voyant-workshop/blob/master/investigating-texts-with-voyant.md.
