corpora

Suggested Ways of Citing Digitized Early Modern Texts

On 1 January 2015, 25,000 hand-keyed Early Modern texts entered the public domain and were publicly posted on the EEBO-TCP project’s GitHub page, with an additional 28,000 or so forthcoming into the public domain in 2020.  This project is, to say the least, a massive undertaking and marks a massive sea change in scholarly study of the Early Modern period. Moreover, we nearly worked out how to cite the EEBO texts (the images of the books themselves) just before this happened: Sam Kaislaniemi has an excellent blogpost on how one should cite books in the EEBO Interface (May, 2014), but his main point is replicated here:

When it comes to digitized sources, many if not most of us probably instinctively cite the original source, rather than the digitized version. This makes sense – the digital version is a surrogate of the original work that we are really consulting. However, digitizing requires a lot of effort and investment, so when you view a book on EEBO but only cite the original work, you are not giving credit where it is due. After all, consider how easy it now is to access thousands of books held in distant repositories, simply by navigating to a website (although only if your institution has paid for access). This kind of facilitation of research should not be taken for granted.

In other words, when you use digitized sources, you should cite them as digitized sources. I do see lots of discussions about how to best access and distribute (linked) open data, but these discussion tend to avoid the question of citation. In my perfect dream world every digital repository would include a suggested citation in their README files and on their website, but alas we do not live in my perfect dream world.

For reasons which seem to be related to the increasingly widespread use of the CC-BY licences, which allow individuals to use, reuse, and “remix” various collections of texts, citation can be a complicated aspect of digital collections, although it doesn’t have to be. For example, this site has a creative commons license, but we have collectively agreed that blog posts etc are due citation; the MLA and APA offer guidelines on how to cite blog posts (and tweets, for that matter). If you use Zotero, for example, you can easily scrape the necessary metadata for citing this blog post in up to 7,819 styles (at the time of writing). This is great, except when you want to give credit where credit is due for digitized text collections, which are less easy to pull into Zotero or other citation managers. And without including this information somewhere in the corpus or documentation, it’s increasingly difficult to properly cite the various digitized sources we often use. As Sam says so eloquently, it is our duty as scholars to do so.

Corpus repositories such as CoRD include documentation such as compiler, collaborators, associated institutions, wordcounts, text counts, and often include a recommended citation, which I would strongly encourage as a best practice to be widely adopted.

Screen Shot 2015-08-05 at 11.15.04

Here is a working list of best citation practices outlined for several corpora I am using or have encountered. These have been cobbled together from normative citation practices with input from the collection creators. (Nb. collection creators: please contact me with suggestions to improve these citations).

This is a work in progress, and I will be updating it occasionally where appropriate. Citations below follow MLA style, but should be adaptable into the citation model of choice.

Non-EEBOTCP
Folger Shakespeare Library. Shakespeare’s Plays from Folger Digital Texts. Ed. Barbara Mowat, Paul Werstine, Michael Poston, and Rebecca Niles. Folger Shakespeare Library, dd mm yyyy. http://folgerdigitaltexts.org/

Mueller, M. “Wordhoard Shakespeare”. Northwestern University, 2004- 2013. Available online: http://wordhoard.northwestern.edu/userman/index.html

Mueller, M. “Standardized Spelling WordHoard Early Modern Drama corpus, 1514- 1662”. Northwestern University, 2010. Available online: http://wordhoard.northwestern.edu.

Mueller, M. “Shakespeare His Contemporaries: a corpus of Early Modern Drama 1550-1650”. Northwestern University, 2015. Available online:  https://github.com/martinmueller39/SHC/

EEBO-TCP access points:
There are several access points to the EEBOTCP texts, and one problem is that the text IDs included don’t always correspond to the same texts in all EEBO viewers as Paul Schnaffer describes below.

Benjamin Armintor has been exploring the implications of this on his blog, but in general if you’re using the full-text TCP files, you should be citing which TCP database you are using to access the full-text files. Where appropriate, I’ve included a sample citation as well.

1. For texts from http://quod.lib.umich.edu/e/eebogroup/, follow the below formula:EEBOTCP michgan

Author. Title. place: year, Early English Books Online Text Creation Partnership, Phase 1, Oxford, Oxfordshire and Ann Arbor, Michigan, 2015.  quod.umich.edu/permalink date accessed: dd mm yyyy

Webster, John. The tragedy of the Dutchesse of Malfy As it was presented priuatly, at the Black-Friers; and publiquely at the Globe, by the Kings Maiesties Seruants. The perfect and exact coppy, with diuerse things printed, that the length of the play would not beare in the presentment. London: 1623, Early English Books Online Text Creation Partnership, Phase 1, Oxford, Oxfordshire and Ann Arbor, Michigan, 2015. Available online:  http://name.umdl.umich.edu/A14872.0001.001, accessed 5 August 2015.

2. For the Oxford Text Creation Partnership Repository (http://ota.ox.ac.uk/tcp/) and the searchable database thereOxford TCP search page

Author. Title. Early English Books Online Text Creation Partnership, phase I: Oxford, Oxfordshire and Ann Arbor, Michigan, 2015 [place: year]. Available online at http://ota.ox.ac.uk/tcp/IDNUMBER; Source available at https://github.com/TextCreationPartnership/IDNUMBER/.

Rowley, William. A Tragedy called All’s Lost By Lust. Early English Books Online Text Creation Partnership, phase I: Oxford, Oxfordshire and Ann Arbor, Michigan, 2015 [London: 1633]. Available online: http://tei.it.ox.ac.uk/tcp/Texts-HTML/free/A11/A11155.htm; Source available at: https://github.com/TextCreationPartnership/A11155/

3. The entire EEBO-TCP Github repositoryGithub EEBOTCP

Early English Books Online Text Creation Partnership, Phase I. Early English Books Online Text Creation Partnership, phase I: Oxford, Oxfordshire and Ann Arbor, Michigan, 2015. Available online: https://github.com/textcreationpartnership/Texts

If you are citing bits of the TCP texts as part of the whole corpus of EEBO-TCP, it makes the most sense to parenthetically cite the TCP ID as its identifying characteristic (following corpus linguistic models). So for example, citing a passage from Dutchess of Malfi above would include a parenthetical including the unique TCPID  (A14872).

(Presumably other Text Creation Partnership collections, such as ECCO and EVANS, should be cited in the same manner.)

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Of time, of numbers and due course of things

[This is the text, more or less, of a paper I presented to the audience of the Scottish Digital Humanities Network’s “Getting Started In Digital Humanities” meeting in Edinburgh on 9 June 2014. You can view my slides here (pdf)]

Computers help me ask questions in ways that are much more difficult to achieve as a reader. This may sound obvious: reading a full corpus of plays, or really any text, takes time, and by the time I closely read all of them, I will have either have not noticed the minutae of all the texts or I will not have remembered some of them. Here, for example, is J. O. Halliwell-Phillipp’s The Works of William Shakespeare; the Text Formed from a New Collation of the Early Editions: to which are Added, All the Original Novels and Tales, on which the Plays are Founded; Copious Archæological Annotations on Each Play; an Essay on the Formation of the Text: and a Life of the Poet, which takes up quite a bit of space on a shelf:IMG_20140604_160953

This isn’t a criticism, nor is it an excuse for not reading; it just means that humans are not designed to remember the minutae of collections of words. We remember the thematic aboutness of them, but perhaps not always the smaller details. Having closely read all these plays (though not in this particular edition: I have read the Arden editions, which were much more difficult to stick on one imposing looking shelf), all I remember what they were about, but perhaps not at the level of minutae I might want to have. So today I’m going to illustrate how I might go from sixteen volumes of Shakespeare to a highly specific research question, and to do that, I’m going to start with a calculator.

A calculator is admittedly a rather old and rather simple piece of technology; it’s one that is not particularly impressive now that we have cluster servers that can crunch thousands of data points for us, but it remains useful nonetheless. Without using technology which is more advanced than our humble calculator, I’m going to show how the simple task of counting and a little bit of basic arithmetic can raise some really interesting questions. Straightforward counting is starting to get a bit of a bad rap in digital humanities discourse (cf Jockers and Mimno 2013, 3 and Goldstone and Underwood 2014, 3-4): yes, we can count, but that is simple. We can also complicate this process with calculation and get even more exciting results! This is, of course, true, and provides many new insights to texts which were otherwise unobtainable. Eventually today I will get to more advanced calculation, but for now, let’s stay simple and count some things.

Except that counting is not actually all that simple: decisions have to be made about what to count and how to decide what to count, and then how you are going to do that. I happen to be interested in gender, which I think is one of the more quantifiable social identity variables in textual objects, though it certainly isn’t the only one. Let’s say I wanted to find three historically relevant gendered noun binaries for Shakespeare’s corpus. Looking at the historical thesaurus of the OED for historical contexts, I can decide on lord/lady, man/woman, and knave/wench, as they show a range of formalities (higher – neutral – lower) and these terms are arguably semantically equivalent. The first question I would have is “how often do these terms actually appear in 38 Shakespeare plays?”

shx minus node words pie chart

Turns out the answer is “not much”: they are right up there in the little red sliver there. My immediate next question would be “what makes up the rest of this chart?” The obvious answer is, of course, that it covers everything that is not our node words in Shakespeare. However, there are two main categories of words contained therein: the frequency of function words (those tiny boring words that make up much of language) and the frequency of content words (words that make up what each play is about). We have answers, but instantly I have another question: what does the breakdown of that little red sliver look like?

This next chart shows the frequency of both the singular and the plural form of each node word, in total, for all 38 Shakespeare plays. There are two instantly noticeable things in this chart: first, the male terms are far more frequent than the female terms, and that wench is not used very much (though we may think of wench as being a rather historical term).
individual node word plurals in Shakespeare (full)

There are more male characters than female characters in Shakespeare – by quite a large margin, regardless of how you choose to divide up gender – but surely they are talking about female characters (as they are the driving force of these plays: either a male character wants to marry or kill a female character). This is not to say that male and female characters won’t talk to each other; there just happens to be a lot more male characters. Biber and Burges (2000) have noted that in 19th century plays, male to male talk is more frequent than male to female talk (and female to female talk). I am not going to claim this is true here, but it seems to be a suggestive model, as male characters dominate speech quantities in the plays. There are lots of questions we can keep asking from this point, and I will return to some of them later, but I want to ask a bigger question: how does Shakespeare’s use of these binaries compare to a larger corpus of his contemporaries, 1512-1662?

It is worth noting that this corpus contains 332 plays, even though it is called the 400 play corpus; some things, I suppose, sound better when rounded up. These terms are still countable, though, and we see a rather different graph for this corpus:
400 play corpus full node words frequencies

The 400 play corpus includes Shakespeare, so we are now comparing Shakespeare to himself and 54 other dramatists.[1] The male nouns are noticeably more frequent than the female nouns, which suggests that maybe the proportions of male to female characters from Shakespeare is true here too. Interestingly, lord is less frequent than man, which is the opposite of what we saw previously. The y axis is different for this graph, as this is a much larger corpus than Shakespeare’s, but it seems like the female nouns are consistent.

One glaring problem with this comparison is that I am looking at two different-sized objects. A corpus of 332 plays is going to be, generally speaking, larger than a corpus of 38 plays.[2] McEnery and Wilson note that comparisons of corpora often require adjustment: “it is necessary in those cases to normalize the data to some proportion […] Proportional statistics are a better approach to presenting frequencies” (2003, 83). When creating proportions, Adam Kilgariff notes “the thousands or millions cancel out when we do the division, it makes no difference whether we use thousands or millions” (2009, 1), which follows McEnery and Wilson’s assertion that “it is not crucial which option is selected” (2003, 84). For my proportions, I choose parts per million.
Shakespeare from Martin's corpus 12.16.10 and Martin's Corpus, normalized plural node words graphed
Shakespeare is rather massively overusing lord in his plays compared to his contemporaries, but he is also underusing the female nouns compared to contemporaries. Now we have a few research questions to address, all of which are very interesting:

  • Why does Shakespeare use lord so much more than the rest of Early Modern dramatists?
  • Why do the rest of Early Modern dramatists use wench so much more than Shakespeare?
  • Why is lady more frequent than woman overall in both corpora?

I’m not going to be able to answer all of these today, though they but let’s talk a little bit about lord. This is a pretty noticeable difference for a term which seems pretty typical of Early Modern drama, which is full of noblemen. If I had to guess, I would say that lord might be more frequent in history plays compared to the tragedies or the comedies. I say this because as a reader I know there are most definitely noblemen, and probably defined as such, in these plays.

So what if we remove the histories from Shakespeare’s corpus, count everything up again, and make a new graph comparing Shakespeare minus the histories to all of Shakespeare? By removing the history plays it is possible to see how Shakespeare’s history plays as a unit compare to his comedy & tragedy plays as a unit. [3]
Shakespeare minus histories compared to shakespeare with histories per million
Female nouns fare better in Shakespeare Without Histories than in Shakespeare Overall, possibly because the female characters are more directly involved in the action of tragedies and comedies than they are in histories (though we know the Henry 4 plays are an exception to that), so that is perhaps not all that interesting. What is interesting, though, is the difference between lord in Shakespeare Without Histories and Shakespeare With Histories. What is going on in the histories? How do Shakespeare’s histories compare to all histories in the 400 play corpus?
history plays, shx vs history plays from 400 play corpus
Now we have even more questions, especially “what on earth is going on with lord in Shakespeare” and “why is wench more frequent in all of the histories?” I’m going to leave the wench question for now, though: not because it’s uninteresting but because it is less noticeable compared to what I’ve been motioning at with lord, which is clearly showing some kind of generic variation.

Remember, we haven’t done anything more complex than counting and a little bit of arithmetic yet, and we have already created a number of questions to address. Now we can create an admittedly low-tech visualization of where in the history plays these terms show up: each black line is one instance, and you read these from left to right (‘start’ to ‘finish’):
Screen shot 2014-06-06 at 4.30.36
And now I instantly have more questions (why are there entire sections of plays without lord? Why do they cluster only in what clearly are certain scenes? etc) but what looks most interesting to me is King John, which has the fewest examples. On a first glance, King John and Richard 3 appear to be outliers (that is, very noticeably different from the others: 42 instances vs 236 instances). Having read King John, I know that there are definitely nobles in the play: King John, King Philip, the Earls of Sudbury, Pembroke, Essex and the excellently named Lord Bigot. And, again, having read the play I know that it is about the relationships between fathers, mothers and brothers – the play centers around Philip the Bastard’s claim to the throne – and also is about the political relationship (or lack thereof) between France and England. From a reader’s perspective, none of that is particularly thematically unique to this play compared to the rest Shakespeare’s history plays, though.

I can now test my reader’s perspective using a statistical measure of keyness called log likelihood, which asks which words are more or less likely to appear in an analysis text compared to a larger corpus. This process will provide us with words which are positively and negatively ranked overall with a ranking of statistical significance (more stars means more statistically significant). Now I am asking the computer to compare King John to all of Shakespeare’s histories. I have excluded names from this analysis, as a reader definitely knows hubert arthur robert philip faulconbridge geoffrey are in this play without the help of the computer.
Screen shot 2014-06-03 at 10.20.23
However, you can see that the absence of lord in King John is highly statistically significant (marked with four *s, compared to others with fewer *s). Now, we saw this already with the line plots, though it is nice to know that this is in fact one of the most significant differences between King John and the rest of the histories.

All of this is nice, and very interesting, as it is something we might not have ever noticed as a reader: because it is a history play with lords in it, it is rather safe to assume that it will contain the word lord more often than it actually does. Revisiting E.A.J. Honingmann’s notes on his Arden edition of King John, there have been contentions about the use of king in the First Folio (2007, xxxiii-xliii), most notably around the confusions surrounding King Lewis, King Philip and King John all labeled as ‘king’ in the Folio (see xxxiv-xxxvii for evidence). But none of this is answering our question about lord’s absence. So what is going on with lord? We can identify patterns with a concordancer, and we get a number of my lords:Screen shot 2014-06-03 at 10.37.59
This is looking like a fairly frequent construction: we might want to see what other words are likely to appear near lord in Shakespeare overall: is my one of them? As readers, we might not notice how often these two words appear together. I should stress that we still have not answered our initial question about lord in King John, though we are trying to.

Using a conditional probability of the likelihood of one lemma (word) to appear next to another lemma (word) in a corpus using the dice coefficiency test, which is the mean of two conditional probabilities: P(w1,w2) and P(w2,w1). Assuming the 2nd word in the bigram appears given the 1st word, and the 1st word in the bigram appears given the 2nd word, this relationship can be computed on a scale from 0-1. 0 would mean there is no relationship; 1 means they always appear together. With this information, you can then show which words are uniquely likely to appear near lord in Shakespeare and contrast that to the kinds of words which are uniquely likely to appear next to lady – and again for the other binaries as well. Interestingly, my only shows up with lord!

Screen shot 2014-06-03 at 10.49.51

This is good, because it shows that lord does indeed appear very differently to our other node words in Shakespeare’s corpus, and suggests that there’s something highly specific going on here with lord, all of which is still suggestive that there is something about lord which is notable. However, I’m still not sure what is happening with lord in King John. Why are there so few instances of it?

Presumably if there is an absence of one word or concept, there will be more of a presence a second word or concept. One such example might be king, but the log-likelihood analysis shows that this is comparatively more frequent in King John than in the rest of Shakespeare’s histories (note the second entry on this list)
Screen shot 2014-06-03 at 10.20.23

Now we have two questions: why is lord so absent, and why is this so present? From here I might go back to our concordance plot visualizations, but this is addressable at the level of grammar: this is a demonstrative pronoun, which Jonathan Hope defines in Shakespeare’s Grammar as “distinguish[ing] number (this/these) and distance (this/these = close; that/those = distant). Distance may be spatial or temporal (for example ‘these days’ and ‘those days’)” (Hope 2003, 24). Now we have a much more nuanced question to address, which a reader would never have noticed: Does King John use abstract, demonstrative pronouns to make up for a lack of the concrete content word lord in the play? I admit I have no idea: does anybody else know?

 

WORKS CITED
Halliwell-Phillipps, J.O. (1970. [1854].) The works of William Shakespeare, the text formed from a new collation of the early editions: to which are added all the original novels and tales on which the plays are founded; copious archæological annotations on each play; an essay;on the formation of the text; and a life of the poet. New York: AMS press.

“Early English Books Online: Text Creation Partnership”. Available online: http://quod.lib.umich.edu/e/eebogroup/ and http://www.proquest.com/products-services/eebo.html.

“Early English Books Online: Text Creation Partnership”. Text Creation Partnership. Available online: http://www.textcreationpartnership.org/

Anthony, L. (2012). AntConc (3.3.5m) [Computer Software]. Tokyo, Japan: Waseda University. Available from http://www.antlab.sci.waseda.ac.jp/

Biber , Douglas, and Jená Burges. (2000) “Historical Change in the Language Use of Women and Men: Gender Differences in Dramatic Dialogue”. Journal of English Linguistics 28 (1): 21-37.

DEEP: Database of Early English Playbooks. Ed. Alan B. Farmer and Zachary Lesser. Created 2007. Accessed 4 June 2014. Available online:http://deep.sas.upenn.edu.

Froehlich, Heather. (2013) “How many female characters are there in Shakespeare?” Heather Froehlich. 8 February 2013. https://hfroehlich.wordpress.com/2013/02/08/how-many-female-characters-are-there-in-shakespeare/

Froehlich, Heather. (2013). “How much do female characters in Shakespeare actually say?” Heather Froehlich. 19 February 2013. https://hfroehlich.wordpress.com/2013/02/19/how-much-do-female-characters-in-shakespeare-actually-say/

Froehlich, Heather. (2013). “The 400 play corpus (1512-1662)”. Available online: http://db.tt/ZpHCIePB [.csv file]

Goldstone, Andrew, and Ted Underwood. “The Quiet Transformations of Literary Studies: What Thirteen Thousand Scholars Could Tell Us.” New Literary History, forthcoming.

Hope, Jonathan. (2003). Shakespeare’s Grammar. The Arden Shakespeare. London: Thompson Learning.

Jockers, M.L. and Mimno, D. (2013). Significant themes in 19th-century literature. Poetics. http://dx.doi.org/10.1016/j.poetic.2013.08.005

Kay, Christian, Jane Roberts, Michael Samuels, and Irené Wotherspoon (eds.). (2014) The Historical Thesaurus of English. Glasgow: University of Glasgow. http://historicalthesaurus.arts.gla.ac.uk/.

Kilgariff, Adam. (2009). “Simple Maths for Keywords”. Proceedings of the Corpus Linguistics Conference 2009, University of Liverpool. Ed. Michaela Mahlberg, Victorina González Díaz, and Catherine Smith. Article 171. Available online: http://ucrel.lancs.ac.uk/publications/CL2009/#papers

McEnery, Tony and Wilson, Andrew. (2003). Corpus Linguistics: An Introduction. Edinburgh: Edinburgh University Press, 2nd Edition. 81-83

Mueller, Martin. WordHoard. [Computer Software]. Evanston, Illinois: Northwestern University. http://wordhoard.northwestern.edu/

Shakespeare, William. (2007). King John. Ed. E. A. J. Honigmann. London: Arden Shakespeare / Cengage Learning.

[1] Please see http://db.tt/ZpHCIePB [.csv file] for the details of contents in the corpus.

[2] This is not always necessarily true: counting texts does not say anything about how big the corpus is! A lot of very short texts may actually be the same size as a very small corpus containing a few very long texts.

[3] The generic decisions described in this essay have been lifted from DEEP and applied by Martin Mueller at Northwestern University. I am very slowly compiling an update to these generic distinctions from DEEP, which uses Annals of English Drama, 975-1700, 3rd edition, ed. Alfred Harbage, Samuel Schoenbaum, and Sylvia Stoler Wagonheim (London: Routledge, 1989) as its source to Martin Wiggins’ more recent British Drama: A Catalog, volumes 1-3 (Oxford: Oxford UP, 2013a, 2013b, 2013c) for further comparison.

An introductory bibliography to corpus linguistics

This is a short bibliography meant to get you started in corpus linguistics – it is by no means comprehensive, but should serve to be a good introductory overview of the field.

>>This page is updated semi-regularly for link rot; if you find any dead links please contact me at heathergfroehlich at gmail dot com. Thanks!<<

1.1 Books (and one article)
Baker, Paul, Andrew Hardie and Tony McEnery. (2006). A Glossary of Corpus Linguistics. Edinburgh, Edinburgh UP.
Biber, Douglas (1993). “Representativeness in Corpus Design”. Literary and Linguistic Computing, 8 (4): 243-257. http://llc.oxfordjournals.org/content/8/4/243.abstract
Biber, Douglas, Susan Conrad and Randi Reppen (1998). Corpus Linguistics: Investigating Language Structure and Use. Cambridge: Cambridge UP.
Granger, Sylviane, Joseph Hung and Stephanie Peych-Tyson. (2002). Computer Learner Corpora, Second Language Acquisition and Foreign Language Teaching. Amsterdam: John Benjamins.
Hoey, Michael, Michaela Stubbs, Michaela Mahlberg, and Wolfgang Teubert. (2011). Text, Discourse and Corpora. London: Continuum.
Hunston, S. (2002). Corpora in applied linguistics. Cambridge: Cambridge University Press.
Mahlberg, Michaela. (2013). Corpus Stylistics and Dickens’ Fiction. London: Routledge.
McEnery, T. and Hardie, A. (2012). Corpus Linguistics: Method, theory and practice. Cambridge: Cambridge UP.
O’Keefe, Anne and Michael McCarthy, eds. (2010).The Routledge Handbook of Corpus Linguistics. London: Routledge.
Sinclair, John and Ronald Carter. (2004). Trust the Text. London: Routledge.
Sinclair, John. (1991) Corpus Concordance Collocation. Oxford: Oxford UP.
Wynne, M (ed.) (2005). Developing Linguistic Corpora: a Guide to Good Practice. Oxford: Oxbow Books. http://www.ahds.ac.uk/creating/guides/linguistic-corpora/

1.2 Scholarly Journals
Corpora http://www.euppublishing.com/journal/cor
ICAME http://icame.uib.no/journal.html
IJCL https://benjamins.com/#catalog/journals/ijcl
Literary and Linguistic Computing http://llc.oxfordjournals.org/

1.3 Externally compiled bibliographies and resources
David Lee’s Bookmarks for corpus-based linguistics http://www.uow.edu.au/~dlee/CBLLinks.htm
Costas Gabrielatos has been compiling a bibliography of Critical Discourse Analysis using corpora, 1982-present http://www.gabrielatos.com/CLDA-Biblio.htm
Members of the corpus linguistics working group UCREL at Lancaster University have compiled some of their many publications here http://ucrel.lancs.ac.uk/pubs.html; see also their LINKS page http://ucrel.lancs.ac.uk/links.html
Michaela Mahlberg is one of the leading figures in corpus stylistics (especially of interest if you want to work on literary texts) http://www.michaelamahlberg.com/publications.shtml; in 2006 she helped compile a corpus stylistics bibliography (pdf) with Martin Wynne.
Lots of work is done on Second Language Acquisition using learner corpora. Here’s a compendium of learner corpora http://www.uclouvain.be/en-cecl-lcworld.html

Corpora-List (mailing list) http://torvald.aksis.uib.no/corpora/
CorpusMOOC https://www.futurelearn.com/courses/corpus-linguistics, run out of Lancaster University, is an amazingly thorough resource. Even if you can’t do everything in their course, there’s lots of step-by-step how-tos, videos, notes, readings, and help available for everyone from experts to absolute beginners.

1.4 Compiled Corpora
Xiao, Z. (2009). Well-Known and Influential Corpora,  A Survey http://www.lancaster.ac.uk/staff/xiaoz/papers/corpus%20survey.htm, based on Xiao (2009), “Theory-driven corpus research: using corpora to inform aspect theory”. In A. Lüdeling & M. Kyto (eds) Corpus Linguistics: An International Handbook [Volume 2]. Berlin: Mouton de Gruyter. 987-1007.
Various Historical Corpora http://www.helsinki.fi/varieng/CoRD/corpora/index.html
Oxford Text Archive http://ota.ahds.ac.uk/
Linguistic Data Consortium http://catalog.ldc.upenn.edu/
CQPWeb, a front end to various corpora https://cqpweb.lancs.ac.uk/
BYU Corpora http://corpus.byu.edu/
NLTK Corpora http://nltk.googlecode.com/svn/trunk/nltk_data/index.xml
1.5 DIY Corpora (some work required)
Project Gutenberg http://gutenberg.org
LexisNexis Newspapers https://www.lexisnexis.com/uk/nexis/
LexisNexis Law https://www.lexisnexis.com/uk/legal
BBC Script Library http://www.bbc.co.uk/writersroom/scripts

1.6 Concordance software
No one software is better than another, though some are better at certain things than others. Much here comes down to personal taste, much like Firefox vs Chrome or Android vs iPhone. While AntConc, which is what I use, is great it is far from the only software available. (Note that these may require a licencing fee.)
AntConc http://www.laurenceanthony.net/software/antconc/
Wordsmith http://lexically.net/
Monoconc http://www.monoconc.com/
CasualConc https://sites.google.com/site/casualconc/
Wmatrix http://ucrel.lancs.ac.uk/wmatrix/
SketchEngine http://www.sketchengine.co.uk/
R http://www.rstudio.com/ide/docs/using/source (for the advanced user)
Anthony, Laurence. (2013). “A critical look at software tools in corpus linguistics.” Linguistic Research 30(2), 141-161.

1.7 Annotation You may want to annotate your corpus for certain features, such as author, location, specific discourse markers, parts of speech, transcription, etc. Some of the compiled corpora might come with included annotation.
Text Encoding Initiative http://www.tei-c.org/index.xml
A Gentle Introduction to XML http://www.tei-c.org/release/doc/tei-p5-doc/en/html/SG.html
Hardie, A (2014) ““Modest XML for Corpora: Not a standard, but a suggestion”. ICAME Journal 38: 73-103.
UAM Corpus Tool does both concordance work and annotation http://www.wagsoft.com/CorpusTool/

1.7.1 Linguistic Annotation
Natural Language Toolkit http://nltk.org& the NLTK book http://www.nltk.org/book/ch01.html
Stanford NLP Parser http://nlp.stanford.edu/software/corenlp.shtml (includes Named Entity Recognition, semantic parser, and grammatical part-of-speech tagging)
CLAWS, a part of speech tagger http://ucrel.lancs.ac.uk/claws/
USAS, a semantic tagger http://ucrel.lancs.ac.uk/usas/

1.8 Statistics Help 1.8.1 Not Advanced
Wikipedia http://wikipedia.com (great for advanced concepts written for the non-mathy type)
Log Likelihood, explained http://ucrel.lancs.ac.uk/llwizard.html
AntConc Videos https://www.youtube.com/user/AntlabJPN
WordSmith Getting Started Files http://www.lexically.net/downloads/version6/HTML/index.html?getting_started.htm
Oakes, M. (1998): Statistics for Corpus Linguistics. Edinburgh: Edinburgh University Press. Baroni, M. and S. Evert. (2009): “Statistical methods for corpus exploitation”, in A. Lüdeling and M. Kytö (eds.), Corpus Linguistics: An International Handbook Vol. 2. Berlin: de Gruyter. 777-803. 1.8.2 Advanced Stefan Th. Gries’ publications: http://www.linguistics.ucsb.edu/faculty/stgries/research/overview-research.html Adam Kilgarriff’s publications: Pre-2009 http://www.kilgarriff.co.uk/publications.htm Post-2009 https://www.sketchengine.co.uk/documentation/wiki/AK/Papers
Baayen, R.H. (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics Using R. Cambridge: Cambridge University Press.

heather froehlich // last updated 06 Feb 2016

Does Shakespeare pass the Bechdel Test?

The Bechdel Test is a measure of how male and female characters are portrayed in cinema and other media. A piece passes the Bechdel test if it:

a) has at least two women in it
b) who talk to each other about something besides a man.

That’s it. Pretty simple, right? Not a lot of contemporary media passes the Bechdel test, rather alarmingly. While I was working out proportions of male and female characters in Shakespeare, I got a number of questions about whether or not Shakespeare will pass. I went looking to see if anyone else had approached this question before. Someone has, but at the time of writing this, their website is down for maintenance.

I have already shown that all of Shakespeare’s plays have 2 or more female characters. But what about “talking to each other about something other than a man”?

I began by searching in WordHoard for all examples of characters with the gender of female who use the lemma form she. In essence I am doing this analysis backwards: I’m asking if there are female characters who talk about something other than a man, then seeing if plays which pass this aspect of the test also feature a female character talking to another female character. If a male character was referred to in some way in the window of +7 words left or right in a way indisputably linking the discussion about the female character to the male character, the play has failed this part of the test.

WordHoard highlights the place in the play where each instance of the lemma she appears; these examples can be cross-referenced by clicking each individual example to call them up in the context of the play by act and scene.

King Lear, for example, fails, with “Why should she write to Edmund?” (IV.v.19)
Screen shot 2013-04-03 at 8.45.57

Titus Andronicus might pass the first part of the test, though:Screen shot 2013-04-03 at 9.14.22
These examples do not show any female character talking about another female character in explicit reference to a man. Male characters (lords) are alluded to, but I read them to not be directly implicated to the newborn baby the Nurse speaks to Aaron about – though you may disagree.

The first cull – do female characters in Shakespeare talk about something other than a man? – left me with the following plays:
Winter’s Tale, Pericles, Macbeth, 2 Henry 6, King John, 2 Henry 4, 1 Henry 6, Tempest, Henry 5, and I’m going to include Titus Andronicus.

1 Henry 4, Richard 2 and Julius Caesar had no examples of the lemma form she, so I will address them here as well.

The next question is “do female characters talk to other female characters in the play?”
Open Source Shakespeare allows you to isolate character’s speeches by name – and gives you the option to show cue speeches and the ability to see these speeches in the context of the play. They have been linked where appropriate.

The Winter’s Tale does not pass the test. Although Emilia and Paulina are talking to each other, they are talking about the king in Act 2 Scene 2.

Pericles does not pass the test: Leonine and Marina are talking to each other, but about Marina’s father (scroll up just slightly from where this link will take you) in Act 4 Scene 1.

Macbeth does not pass the test either, as The Gentlewoman talks about Lady Macbeth, but to the Doctor, who is presumably male, in Act 5 Scene I.

2 Henry 6 does not pass the test, as the female characters do not talk to each other.

King John does not pass, because of an interchange between Constance and Queen Elinor in Act 2 Scene I, in which they discuss John, Elinor’s son.

2 Henry 4 also does not pass, for two reasons: one, this interchange between Lady Northumberland and Lady Percy has them talking about the King in Act 2 Scene 3,  and two, because of this interchange between Doll Tearsheet and Hostess Quickly from Act 2 Scene 4, in reference to Pistol.

1 Henry 6 does not pass the test because the female characters do not talk to each other.

The Tempest also does not pass the test because the female characters do not talk to each other. (I am considering Ariel a female character here; this is still very much up for debate, and this may automatically disqualify The Tempest overall.)  Miranda and Ariel are not in conversation.

Henry V does pass the Bechdel Test, due to this discussion (in French) between Katherine and Alice from Act 3 Scene 4.

Titus Andronicus ultimately does not pass the test due to this conversation between Tamora, Lavinia and Bassanius in Act 2 Scene 3.

1 Henry 4 does not pass because the female characters do not talk to each other.

Richard 2 passes because the Queen and her ladies “are carefully not talking about Richard” as @angevin2 kindly points out; they are instead talking about garden sports in Act 3 Scene 4.

Julius Caesar does not pass because the female characters do not talk to each other.

By and large, Shakespeare does not pass the Bechdel test: but two plays do – and it’s not the plays I ever would have expected. However, I should point out I might be wrong here: like I said above, I did this backwards, by finding plays that had female characters talking without mentioning male characters, then checking to see if these plays did show two female characters in conversation. If you have a better solution for finding out if Shakespeare passes the Bechdel test, I am all ears!

EDIT (18 June 2015)

Some recommended further reading:
Selisker, Scott. (2014) “Literary Data and the Bechdel Test“, from the What Is Data in Literary Studies? colloquy, Modern Language Association annual meeting, Chicago, IL.

Mariani, Daniel. (2013) “Visualizing The Bechdel Test“. Ten Chocolate Sundaes blog post, 24 June 2013.

Agarwal et al (2015) “Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test“. Human Language Technologies: The 2015 Annual Conference of the North American Chapter of the ACL, pp. 830–840, Denver, Colorado, May 31 – June 5, 2015.