David Hoover, Stephen Ramsay, Algorithmic Criticism

Science has finally become a tangible reality in the literary world. The development of both Principal Component Analysis and Cluster Analysis technologies beg to change the face of modern criticism and literary interpretation across the board of higher education and beyond. Just as the smallest unit of measurement in science (currently), is the atom, the smallest unit of measurement in literature is the word. “Words have the advantage of being meaningful in themselves and in their significance to larger issues” (Hoover). These technologies allow readers and critics alike to compare the frequency of words used in certain texts. We can even compare the same authors now; by imputing one piece of data (literature) from an author in one year and comparing it to his work from two decades later, we can come to verifiable conclusions about former theses upon which we could only speculate. Aside from the philosophical implications of condemning all literature to a fate to be determined by artificial intelligence, David Hoover and Stephen Ramsay elude to the function of Principal Component Analysis and where it may have a home in the world of higher literary criticism.
Principal Component Analysis “compresses information about the frequencies of the one hundred most frequent words as possible into a small number of unrelated new variables” (Hoover). Analysts use this data for an assortment of studies; they compare gender word frequencies, word phrase frequencies, and further expand upon how the frequencies of words can point to a hypothesis about the text (what was formerly known as a thesis), that can be fact-checked in the same ways a science experiment can. Neither Hoover nor Ramsey claim to assert that this analytical technology can confirm that women were one way or another in the 17th century, but they can further crystallize or confirm invalid the evidence critics have used in their own interpretations of text about women during this time. By finding measurable results from a literary text, Principal Component Analysis has rendered useless countless amounts of former literary criticism. That is assuming that Principal Component Analysis becomes the end-all be all answer to what makes textual interpretation valid. As pointed out by Ramsey, “Science differs significantly from the humanities in that it seeks singular answers to the problems under discussion,” while literary critics don’t always seek one, definitive answer to textual interpretation (and rarely do) (Ramsey). “Woolf critics are not trying to solve Woolf. They are trying to ensure that discussion of The Waves continues into further and further reaches of intellectual depth.”
In this moment in my own textual analysis of these articles I am not only reminded of Christopher Nolan’s Inception, but also of Darren Aronofsky’s Pi (1989). Is it permissible for me, as a reader of criticism, to project upon this text my own interpretation or meaning? I will do so, and should I find that it is unbefitting for a student of literary criticism to insert personal pronouns into the mix, I shan’t do so in the future. That said, Darren Aronofsky’s Pi features a mathematical genius seeking to solve for pi. The secrets of his quest soon leak, and he becomes the point of pursuit for stock market tycoons and orthodox Jews seeking his answers to point to a direct interpretation of the Torah. The zealots operate under the assumption that they can use mathematics to interpret text. In so doing, they will find a direct message from God about the coming of the savior (or so they believe). If we are using Principal Computational Analysis for the works of St. Thomas Aquinas and we find that “CPA showed ‘presence’ is that which toward every formation tends,” could we not use the same technology on even more profound works of literature to find the secrets we so desperately seek from a higher source about our conception as higher thinking human beings? The ramifications of this technology are bound to be felt within the next several decades of our existence as artificial intelligence becomes more of a reality and less of a subject matter for dystopian novels. That said, at the end of Pi, the main character (upon the brink of discovering all the secrets mathematics and religion have to offer), drills a hole into his head. In the final scene of the movie, he is sitting on a park bench, Forest Gump-like, enjoying the breeze of the wind as it makes its ways through the trees. Is our quest for meaning a search in the wrong direction? Aronofsky would potentially say so; as the secrets any God or creator may want us to know lie outside the depths of analysis, both computational and otherwise.

written by Shawna Marie Rodgers

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