Shakespeare’s Language: A Corpus Linguistics Approach MOOC

Course: Shakespeare’s Language: Revealing Meanings and Exploring Myths
Length: 4 weeks, 3 hrs/wk
School/platform: Lancaster University/FutureLearn
Instructor: Jonathan Culpeper, Andrew Hardie, Sean Murphy etc.
Quote:
William Shakespeare is a global phenomenon, yet there is actually relatively little work specifically devoted to his language, and even less deploying the latest techniques from linguistics.
On this course, you will explore Shakespeare’s language and, more generally, the language of his time. Over four weeks, you will be introduced to “big data” corpus methods (methods that use computers to explore large volumes of language data) which you can use for your own investigations, and will explore how words and meanings pattern across plays, characters, and more.
Along the way, you will find out why various beliefs about Shakespeare’s life and language–like that he coined an extraordinary number of new words–are actually myths.

I’ve taken several moocs on Shakespeare over the years, from the thorough reading of Young Love/Tragic Love offered by Wellesley, to the more emotional focus on individual scenes via Adelaide University’s Shakespeare Matters, to Stephen Greenblatt’s cultural and historical approach of Othello’s Story. Now add to those this linguistic examination of the language used in, primarily, the plays, with the assistance of corpus linguistics – augmented by a bit of myth-busting.

We started with a general examination of Early Modern English and the printing methodologies in use during Shakespeare’s time. That, combined with frequent use of CPQ Web to look up word frequencies and collocations, helped set the stage for the myth busting segment: Did Shakespeare really invent 1700 new words? When viewed through software including the amassed work of the period, that number seems to fall, and other possibilities (collaboration, printing-induced revisions, the difficulty of recording spoken language), it falls even more. Other sections looked at questions about Shakespeare’s vocabulary – was it more extensive than other playwrights of the day? – and his supposed lack of training in Latin.

It was great fun to explore these questions using the tools made available in the course, with the help of videos providing detailed instruction. I was surprised to find I still had a CPQ Web account from back in 2014, when I took Lancaster’s Corpus Linguistics mooc, one of the first moocs I ever took (and, I still say, one of the best designed, particularly for learners of different levels from novices like me to professional linguists and professors looking to add CL skills). All I had to do was add permissions for the Shakespeare corpora, and I was good to go.

The focus on language gave a different way of looking at Henry IV, Part I. Is the focus on Wales more about the Elizabethan view, or about an individual character? How can Falstaff’s “verbal dexterity,” or just his oaths, be examined in context? These sections were very brief, but served as introductions that made me want to know more.

The lectures were very short (generally about 6 minutes) and highly structured in the traditional manner: tell ‘em what you’re gonna tell ‘em, tell ‘em, then tell ‘em what you told ‘em. Futurelearn doesn’t do grades for auditors, but does have periodic “Check Your Knowledge” quizzes which are quite sufficient for keeping track of which points you’ve retained and which you need to review.

As a fun postscript: After I completed the material, an article came across my twitter feed (I can’t find exactly how, one of the literary/language accounts I follow must have retweeted it) titled ‘How Data Science Pinpointed the Creepiest Word in “Macbeth”’, written by Wired columnist Clive Thompson. It reports on an academic article by Jonathan Hope and Michael Witmore titled “The Language of Macbeth” on keywords in the play, in particular, an examination of the word “the” and how it contributes to the “creepiness” of the play. This is exactly the kind of thing I’d just been learning about! It’s quite exciting to come across something in the wild that relates so directly to course material.

The scheduled portion of the course was over; we were in the 10-day “catch up” period included (for those of us auditing) but I posted a comment anyway, to see if anyone else had any thoughts on this, particularly the question I didn’t really see answered in the article: how does that keyword statistic stack up against the other plays, particularly the tragedies? A student responded with the results of his investigation, which was helpful. Then, to my surprise, Prof. Andrew Hardie, who’d guided our CPQ Web adventures via video and provided discussion board feedback throughout the course, replied in detail. He put the article in context and recommended some alternate approaches using corpus linguistics combined with grammatical theory to examine the question of informational vs interpersonal interactions. It was a real treat to see this kind of response; this is what moocs can be at their best.

There’s frequently a negative bias towards data-driven analysis of literary work. I remember reacting strongly to Pam Houston’s exasperation on hearing about “distant reading” (a specific type of analysis using similar technology, as far as I can tell) in her article “What Has Irony Done For Us Lately?” from Pushcart 2019. Rather than replacing close reading – which, by the way, itself was a new technique less than a hundred years ago  according to the Yale Theory of Literature OCW – corpus linguistics and related data-driven methods offer other ways of examining questions of meaning as well as questions of literary history and development.

I’d highly recommend this course to anyone who’d like to think about Shakespeare in a way that’s perhaps different from the hushed reverent tones of traditional literary analysis, and to anyone who enjoys thinking about how language works to convey meaning. I only wish it had been more extensive; perhaps there will be other moocs that continue to explore questions like these.

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