. . . Polite literature is in the last analysis emotions; and all its charms and message must be spiritually discerned.

The first requisite, therefore, in teaching literature, would seem to be some certain means of reaching and engaging the sensibilities more directly. So far as their exercise is called for in teaching science the method in general use assures it. By it each student acquires not only systematic knowledge concerning the aspects and nature of the phenomena considered,—which is of the understanding, but also experimental knowledge of each quality and process,—which is of the feelings and becomes part of himself.

(Sherman, viii)

Willa Cather wrote a scathing account of her University of Nebraska-Lincoln literature professor Lucius Sherman, who wanted to reduce literature to its irreducible: the word. Sherman wrote a text in 1893 called *The Analytics of Literature*, where he advocated a mathematical and statistical approach to the study of literature. Such a scientific process, where a student would break the text into its component parts, would be guided by a teacher in a laboratory setting, where the elemental sources of the poem, the words, would be the materials of experimentation. Such a study could only lead the student to understand the sublime emotions that literature inspires. Sherman proposed a few experiments, including analysis of word count and frequency to devise statistical curves to show “force” and “tone quality.”

When I read his preface, I was acutely reminded of a scene in *The Princess Bride*, where Count Rugen tortures the Dread Pirate Robert in the Pit of Despair. As Westley’s life is sucked away by the count’s Machine, he is directed to “be totally honest on how the Machine makes you feel. . .Remember this is for posterity, so, be honest.” Cather must have felt that her poetic life was sucked out of her by force curves and frequency lists. I wonder what Professor Sherman would do if he could use a concordance program like TXM or build his own program in R. Texts by Shakespeare, Chaucer, and Browning are left, like the Dread Pirate Robert, “mostly dead,” their elemental life sucked out of them.

When Leibniz took a crack at trying to devise a symbolic language for mathematics so that he could one day create a perfect computing device, I wonder if he wanted to reduce all concepts to a symbolic logic, or to a Boolean if/then or true/false construct of concepts. Already, language and literature are in themselves symbolic, pointing to a truth outside of the word or sentence or phrase or line of poetry itself.

If one could peacefully cohabitate with Leibniz, Boole, Gödel, Cather, and Sherman, it’s not going to a battle to the death, but to the pain, and the pain is going to come from building the code that will allow the frequency lists and concordances to reveal something about the beauty or sentiment or sensation of the text. The trick, then, to becoming a “computing humanist” is to embrace both the mathematics of language and poetry and the language of discrete and symbolic mathematics.

I remember crying helplessly as a second grader trying to understand how to borrow when subtracting, and I suspect that all of my math anxiety comes from that moment. I understood that the 1 needed to be borrowed, but every explanation for the construct that allowed for that was dissatisfying and mystifying. What part of number theory did I not understand as an eight year-old? As soon as I got into more conceptual mathematics in trigonometry and calculus, I was much much happier, and started to enjoy the symbolic language of math. Perhaps Cather, francophile that she was, would enjoy the symbolic language of R, the computer language that would allow her to strip a text down to its parts in a few minutes of processing, so that the grunt work of finding “the least common multiple of *Hamlet* and the greatest common divisor of *Macbeth*,” could be done by a computer, counting it all out at last, so that the untangling of the “yarn” would be easier and easier.

The essence, though, of the story is still there for the analyst to pick through. Without a sense of the symbolic, the tune of the meaningful, the taste of the poetic, or the perfume of the aesthetic, the results of such calculations and computations are meaningless, and the analyst must set to work. The program cannot interpret, it can only offer up what the programmer asks for. As the women at Bletchly Park had to, so we must, as computing humanists, search for meaning in the data.