Digital Humanities: "Tools to Think With"

This week I'll be turning back to look at what can be achieved through use of Digital Humanities methodologies, and the first article I'll be reading is "Stylistic Analysis and Authorship Studies" by Hugh Craig. 

The concept of using technology to identify stylistic patterns in a corpus is both fascinating and unheard of, considering that such a feat would take considerable work without computer programs in a time when "with no way of assembling and manipulating counts of word-variables, researchers in earlier periods assumed that very common words varied in frequency only in trivial ways among texts." Now, however, a computer can be programmed to detect intricacies that go unnoticed by human beings, DH methodologies introduce a whole new world of possibilities to linguistics studies. To this note, Craig defines computational stylistics as follows:

Computational Stylistics aims to find patterns in language that are linked to the processes of writing and reading, and thus to "style" in the wider sense, but are not demonstrable without computational methods.

In other classes in the Kean English and Writing Studies M.A. program, we have had extensive discussions on the tragedy that occurs when writing is limited to the English classroom, as well as the misfortune English departments suffer as being compartmentalized into "literature people." This chapter offers the perfect counter to this issue as stylistics. In the same breath that Craig explains that stylistics can be monitored to study associations in Shakespeare plays, the field is also important in courtrooms for the purpose of deciphering. Who says that English majors sit around analyzing literature all day?

That being said, I'm an English literature geek and analyzing literature is important to me. Craig exemplifies one potential use of stylistics by analyzing Shakespeare's plays in order to study association and differences, based on dialogue. I found this study fascinating, and I'm excited to learn more about DH methodologies because this is exactly how I'd like to tie the tools into my own work. I don't know if I'm communicating how cool I think this is--- this is SO COOL. Shakepeare lived roughly 450 years ago. His works have been analyzed a million different ways and it's only now, in our lifetime, that we have the technology to come up with entirely new scholarship. And this isn't just about Shakespeare-- as I mentioned earlier, we can use the computer to make so many things happen. This might just revolutionize the English department.

As is the case with everything, there is always room for error, especially considering that all of this work still comes down to human interpretation. Craig allows the consideration that "at best, [this methodology provides] a powerful new line of evidence in long-contested questions of style; at worst, an elaborate display of meaningless patterning, and an awkward mismatch between words and numbers and the aesthetic and the statistical." Something worth considering, but worthy of keeping us from trying nonetheless!

This all being said, every point has a counterpoint, so enter the challenger: Stanley Fish. Ah, Stanley Fish. Is it an English department discussion without Fish? I'd argue not. Craig mentions Fish in conjunction with a discussion on the challenges against linguistics. Scholars such as Fish see a fundamental flaw in considering only stylistics when analyzing an article, as he feels that this divorces meaning from the text:

[Fish believes that] when abstracted from this setting [stylistics] refer to nothing but themselves and so any further analysis of patterns within their use, or comparison with the use of others or in other texts, or relating of them to meaning, is entirely pointless. Fish does not deny that there may be formal features which can enable categorical classification such as authorship (and so he is less hostile to authorship studies using computational stylistics), but he insists that these features cannot offer any information of interest about the text – just as a fingerprint may efficiently identify an individual but reveal nothing about his or her personality.

Craig respectfully nods to Fish's genius as a humanist and scholar, and recommends Fish as crucial reading for anyone interested in stylistics, so that the young scholar is made aware of potential pitfalls along the way of research. However, he also notes that stylistics is not necessarily anti-humanist. Stylistic clues can reveal interesting facts about a text, but it's important that the researcher doesn't get caught up in the pieces of the puzzle and forget the big picture.

In general, stylistics can reveal trends and ideas worthy of study. Craig points out that "it's methods allow general conclusions about the relationship between variables," and this isn't something that should be dismissed easily. Likewise, stylistics shouldn't be thought of a merely quantitative: as Craig argues throughout his chapter, qualitative research can be derived from the numbers. I liked how he explained the field in this particular paragraph:

There is a strong instinct in human beings to reduce complexity and to simplify: this is a survival mechanism. Rules of thumb can save a great deal of time and effort. Stylistics is born of this instinct. What seems hard to explain in the individual case may be easier to understand when it is seen in a larger context. If these elements can be put in tabular form, then one can harness the power of statistics and of numerous visualizing and schematizing tools to help in the process of finding patterns.

Craig splits off in the latter part of the chapter to discuss humanities computing in relation to the question of authorship, and makes note of Shakespeare, Homer, and the Bible, to make a point of the things that may be clarified through computing. Any English major, whether they agree or not, can tell you about the debate surrounding Shakespeare, which questions if he wrote every book that is attributed to his name. Although the methodology is not infallible, humanities computing may provide answers, or at least new ways of studying the question. Looking into such questions through a new lens in fascinating, and who knows the ideas that may be derived from the new tools we have at hand!

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The second chapter I've chosen for this week is "Print Scholarship and Digital Resources" by Claire Warwick. In this article, Warwick gives the best term I've yet found to describe the DH methodologies: "tools to think with." (I liked it enough to make it the title of this post!)

DH methodologies certainly are tools, and it's for this reason that scholars should not be afraid. One of the fears that permeates the literary world is the fear that the DH are going to knock out the old methods of study, and Warwick purports that this is not, and will never be, the case. To support her case, she refers back to the 1990s when people feared that the book was in danger of going extinct. I myself remember in the mid-2000s when e-books became popular and people, myself included, fretted that this was the end of paper books. In 2017, we see that this is not the case. The world is changing, chain booksellers are struggling, but the paperback is not going anywhere. In the same way, Warwick argues, we should not worry about the traditional methodologies.

The computer is a tool, and should be used accordingly but, sadly, many critics refuse to try. In a particularly interesting paragraph, Warwick documents how scholars are presented with the wonders that technology can produce, but these wonders aren't personal, and she suggests that this may be due more to disinterest and misunderstanding, than to fear. Rather than "apparent conservatism," it may be that "Users have been introduced to all sorts of interesting things that can be done with computer analysis or electronic resources, but very few of them have been asked what it is that they do, and want to keep doing, which is to study texts by reading them." If reading is still important, the technology should serve the reader, just as it serves the programmer and the coder; "computers are of most use when they complement what humans can do best." Computers cannot do everything, and programs are limited. As Warwick points out, a computer cannot recognize figurative use of language, and different people may interpret figurative language differently. This is where human interaction with data becomes of utmost importance.

Throughout the rest of Warwick's article, she continues to defend both the DH, as well as the importance of human interpretation, and makes a compelling case for marrying the two together to successfully move English departments into the future, that is, if scholars are brave enough to take the plunge.