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Final

Final Project

For my Final Project I set out to answer the research question I have been attempting to tackle all semester. My question deals with the core ideas and metaphors represented in both C.S. Lewis’s and J.R.R. Tolkien’s magna opera. Both writers were heavily influenced by their beliefs, Tolkien a devout Catholic his entire life, is a often credited as one of the largest factors in Lewis’s conversion from Atheism to Christianity, and later his writings as a Christian Apologist. Both writers had extensive amounts of published and unpublished literature, how could this large part of their lives, seem into their writing. For Lewis, the metaphors are quite clear, Aslan clearly represents a higher being, but what do his actions and his depiction reflect about Lewis’s religious ideas themselves. Tolkien similarly creates deities in his books, and to the same extent as Lewis, writes a Christ-like rebirth scene for one of the higher being protagonists. Surely, these depictions can tell us something about the writers themselves, surely they can reveal ideas upon the writes beliefs. I set out to find answers.

A clear statement of my guiding question are as follows:

1.How do Tolkien and Lewis differ in the ways their writing reflects their spirituality?

2.If so, what can we learn through analysis of their writing?

Furthermore, the individual analyses I did to find these answers

a.Differences in collocates between Narnia Children and Hobbits

b.Similarities in stylometrics regarding the rebirths of Aslan and Gandalf

c.Collocates of heroes during the final scenes of the books

d.Finally, difference in style, and word choice, between fiction and non-fiction works of both authors

The first question, was actually recommended to me by professor Faull. It brings up an interesting perspective because the Hobbits and the children both play pseudo-hero roles, often being outshone by their deified counterparts, Gandalf and Aslan respectively, yet they are also both supposed to personify the most ideal, noble, heroic, and even holy characteristics.Screen Shot 2016-04-29 at 10.54.43 AMScreen Shot 2016-04-29 at 10.42.27 AM

On the left, you will find collocates of Lucy, the only child present in all the books of Narnia, and on the right, you will find collocates of Frodo, the most protagonist Hobbit in Lord of the Rings. Upon a glance, and only from the small screen shot I have provided, a viewer can tell that words like “dear” “please” seem far more pleasant than “cried” (it is worth mentioning that some of the words not pictured here for Lucy were “nice” and “kind”, while some of the other more popular words for Frodo were “poor” and “saddened”). This reminded me of data I presented earlier in the year, that yielded similar results, but with completely different parameters.

Screen Shot 2016-05-11 at 12.20.22 AM Screen Shot 2016-05-11 at 12.20.33 AM

So here, as I noted in my midterm review, Lewis uses words to belittle his christlike character, while Tolkien to the same effect, empowers his satan-like character. Both create a narrative where the weaker protagonist must overcome the stronger antagonist; clearly biblical references especially considering both protagonists sacrifice themselves and are brought back to life. Where the authors do differ is in the previously mentioned depiction of the children and the Hobbits. Both play similar roles in the stories, eventually becoming the main protagonists and heroes, but through the analysis one can tell that along their journey Tolkien seems to humanize the Hobbits by exemplifying their flaws, while Lewis reg-ifies Lucy.

Does this mean that Lewis recognizes the inherent good in people mentioned in the bible and that Tolkien instead recognizes every humans tendency to sin also mentioned in the bible? Both depict their heavenly figures in similar ways, but the ways in which they depict their humans in quite interesting.

Another interesting plot development I discovered about the works, was their depictions of their characters as the plots ended. Again using Frodo and Lucy, Professor Faull suggested I checked the collocates towards the end of each respective work.

Screen Shot 2016-05-11 at 12.57.33 AM Screen Shot 2016-05-11 at 1.00.09 AM

While Lewis’s characters grow in maturity, wisdom, and fortitude, Tolkien’s Frodo seems to be drained of these qualities throughout the end of the novel. And given the scene in Mount Doom anyone could note the degradation of Frodo, I think it is important to point out that this decline was not as sharp as it might have seemed. In fact, in the second half of the 3rd book, almost all of Frodo’s collocates are negative. Lucy on the other hand, is continuously regarded even more highly.

I went further and also compared the collocates of both Aslan and Gandalf. Screen Shot 2016-05-11 at 1.03.39 AM Screen Shot 2016-05-11 at 1.04.46 AM

Aslan, towards the end of Narnia, seems to lose importance, and the emphasis is shifted to Lucy and company. Gandalf, on the other hand, maintains all of his clout, with Frodo staring with “eyes full of terror at Gandalf”.

If you consider all of this information together it makes sense. Through my analysis, we learned that Tolkien places far more emphasis on his deities, while often showing the flaws of his human characters. Lewis conversely, eventually has his human characters surpass his deity. All of this can be argued and drawn from the data above.

We also know that Lewis was an former atheist, who converted to Catholicism, which would explain how his writings could reflect the declining powers of the works god. Tolkien, a lifelong Catholic, even at the ends of his work, maintains the power and place of his deities.

Based on these conclusions, I would state that, while it is widely accepted that the Chronicles of Narnia are a biblical story, The Lord of the Rings is more religious.

 

 

My Corpus: https://drive.google.com/drive/u/1/folders/0B4ATX3PFP8CYOV9nN01kdV9UVUE

 

 

Bibliography

Jiayu Huang– Lord of the Rings parsed and cleaned text

All other texts were downloaded from:https://b2dbuntu.wordpress.com

Categories
"machine reading"

A Reflection on Machine Reading and Subjectivity

After a long period of deep pensive contemplation, I have emerged from my thoughts with a new found perspective on not only the digital marking of texts, but digital text reading as a discipline. The prompt for this blog asked “How has the process of stylometry and marking up affected your understanding of the corpus?”, and I would like to interpret this as my understanding of “the” corpus, not “my” corpus.

Regarding this, Pierazzo wrote “what we choose to represent and what we do not depends either on the particular vision that we have of a particular manuscript”. This brings up a brilliant point relative to all the work we are doing. Everything we do in this field is highly subjective. We choose the parameters, we choose the document, we choose the outcome. Much like the field of statistics, we set out to find proof to validate answers to questions. We propose research questions in order to give motivation and a frame to work in, but the honest truth is that in order to propose that research question, one must know about the works in question, and therefor must have biases. I would argue that 99% of the time research questions are proposed, researchers already have an answer in their mind, and this can shade their processes.

Pierazzo also wrote about the documentary digital editions of texts in her article, for example, stating they functioned “as the recording of as many features of the original document as are considered meaningful by the editors, displayed in all the ways the editors consider useful for the readers”. This is blatantly subjective, but not to a fault. It is just a fact, that the digital model of texts does not exist to escape subjectivity but the digital model exists to simplify analyses; “a model must be simpler than the object it models, otherwise it will be unusable for any practical purpose”

This is not meant to be a sentencing that all digital humanists will never be able to escape the binding of subjectivity, but instead, and I think Pierazzo would agree, is meant to be a simple reminder that we must keep in our mind when both reading analyses and analyzing ourselves. Each researchers individuality is what allows us to take on so many perspectives and attempt to understand them.

Keeping all this in mind, how has these processes affected my understanding of the corpus? Primarily, everything, including the corpus, is subject to biases. In order to illustrate this, I have a dendrogram of a particular section of Lord of the Rings. This section is separated into different sub-sections, once by the original creator of this digital text, and then a I combined all of these and had lexis, cut out sections using its own system. These were the results, Screen Shot 2016-04-27 at 10.37.32 AM

The higher links are unimportant, but instead focus upon the fact that all of the sub-sections created by lexis are clustered, and all of the sub-sections that came distributed this way are clustered. Keep in mind that all of these are the same sections of text. This is simply proof that the corpus is an extremely subjective part of the research, just as much as the outcomes.

Next I went to go put this to work myself. I worked within the sections Tom Bombadil, in Lord of the Rings, and marked up nature related terms in his speech. Screen Shot 2016-04-27 at 10.43.50 AM

I then wanted to compare the density of these references to those in his songs, but this is when I reached my large realization with digital mark up in oxygen; what is the end game? How would I complete my analysis? I think that oxygen needs to embed a way to analyze your marked up work into the actual program.

Drawing full circle now, I think that my work with oxygen and lexos have taught me an important thing that Professor Jakacki stressed during her presentation. Because one can mold the corpus in anyway possible, there is no end to the possible analyses one could do. It is important to keep the research question in perspective, and ask, when is enough, enough.

Categories
Uncategorized

Sentiment Analysis: Can Machines Read Emotions

“It is manifestly impossible to read everything, and it has always been so. The utility of the digital corpus— despite its vaunted claims of “increased access”— only serves to make the impossibility of comprehensive reading more apparent.”

 

Of all the articles we have read, I believe this is the more relevant, insightful, and true statement this semester, by any author. Ramsey is spot on in his defense of the digital humanities, because in one statement here, he has both admitted its flaws and exemplified its purpose. The goal of Digital Humanities is not to gain comprehensive readings on the texts being analyzed, but instead to provide data that humans could never do. As he puts it, “it is unlikely that a human being, even if asked to name only the top three words in each text, would produce these lists precisely as the machine gives them to us”. This is the true power of digital analysis, it provides information otherwise unobtainable.

Similarly, regarding comprehensive readings, humans possess the ability to evaluate semantic meanings of texts and understand context on a level a computer could never achieve. Ramsey, discussing students biases on books, says “Books come to them as high or low, deep or shallow, hard or easy, read “for pleasure” or read “for class;’ with dozens of gradations in between”

This kind of emotional or semantic analysis is deeply and inherently human, and something that a computer would not be able to comprehend in full. Yes a computer can understand that certain words are inherently shaded one way or another, but it is prone to mistakes. Awesome, for example, could be used to describe Hiroshima or your cousins wedding last weekend. Someone’s heart can skip a beat when they are about to crash a car, or when they are leaning in for a kiss. Words, phrases, context, language, are all inherently human and require complex thought in order to understand.

For these reasons, I just believe it is currently beyond the capacity of computers to analyze semantics and emotions, given the evidence presented by Topic Modeling.