a.) My corpus is from one of the pre-packaged sets that Professor Faull gave us as an example. While this may seem like an easy way out, I have always had a vested interest in civil rights. Growing up in Birmingham, Alabama, and having grandparents who lived there during the 1950’s, I have always been interested in the civil rights movement in the United States. Also, I am half Palestinian. My grandfather on my mom’s side came to the U.S from Ramallah Palestine when he was 15 after his family was removed from his house at gunpoint by militants. Having been told his story from a young age, the issue of human rights has always been one I have been passionate about. All of this being said, I am still working on adding to my corpus, but for now I spent a good amount of time analyzing what I have in Voyant and Jigsaw.
b.) Voyant provides many different ways to interact with a vast amount of text, I had a lot of interesting thoughts while playing with my data input. One of the first tools that shows up when one uploads their corpus is the “Cirrus” tool. It shows a puzzle-like picture of words where size corresponds to frequency of mention within the entire corpus. It gives an idea of what the central words in a piece or a set of works may be, but it is not an end all be all for the message as it’s simply a frequency representation. Below is the Cirrus for my entire corpus.
Another part of Voyant that I found interesting was the “terms” visualization. It shows the most frequently used terms in a list, but then on the side it shows relative frequency and trends for which documents they were most often used in and at what point in those documents. It is shown below as well. I found this very interesting as it’s not necessarily a takeaway one would have or even contemplate when reading the documents themselves.
c.) I found Jigsaw to be interesting in a very different way than Voyant. I felt as though it was pushing me to make connections between aspects of the texts, as well as the individual texts themselves. The word tree tool was fascinating as it allowed me to gain perspective on the context in which words were being used across texts throughout the corpus. For example, below is a screenshot of what happened when I searched the word “People”, which as voyant shows above, is the most often used word throughout the corpus.
As can be seen, this image shows tons of different and unique uses of the word people in the corpus, and even this plethora is only 15% of the total usage overall. I also found the document grid viewer very thought-stimulating as it allowed the user (me) to sort the documents based on importance for a variety of factors.
d.) Maybe I am biased because I have likely spent more time with and have a greater understanding of how to use Voyant, but in my opinion its interface is so much more user friendly than that of Jigsaw. It presents easy to read menus and tools with adjustability of features without having to x-out of one window, research a word, and open a new window to see a new visualization. There are some levels of detailed text analysis that I thought Jigsaw was useful for to supplement the limitations of Voyant, and perhaps those are magnified the deeper one goes into analysis, but I found most of the things I wanted to do on Jigsaw, I could find similar data presentations on Voyant in more user friendly ways.
e.) I think that working with these two platforms has greatly contributed to the “multidimensional viewpoint” as Clement put it. I feel that I have garnered insights about these sets of textual data that I could have never surmised simply from reading each individually. The ability to visualize large sets of the data in quantitative and qualitative graphs, tables, etc. allows for a more comprehensive understanding of the meta characteristics of the corpus. It also sheds light on what may be “plausible truths” about the texts and works that would otherwise go undiscovered.