The Digital Parisian Stage is now on GitHub

For the past five years I’ve been working on a project, the Digital Parisian Stage, that aims to create a representative sample of Nineteenth-century Parisian theater. I’ve made really satisfying progress on the first stage, 1800 through 1815, which corresponds to the first volume of Charles Beaumont Wicks’s catalog, the Parisian Stage (1950). Of the initial one-percent sample (31 plays), I have obtained 24, annotated 15 and discarded three for length, for a current total of twelve plays.

At conferences like the Keystone Digital Humanities Conference and the American Association for Corpus Linguistics, I’ve presented results showing that these twelve plays cover a much wider and more innovative range of language than the four theatrical plays from this period in the FRANTEXT corpus, a sample drawn fifty years ago based on a “principle of authority.”

Just looking at declarative sentence negation, I found that in the FRANTEXT corpus the playwrights negate declarative sentences with the ne … pas construction 49 percent of the time. In the twelve randomly sampled plays, the playwrights used ne … pas 75 percent of the time to negate declarative sentences. Because this was a representative sample, I even have a p value below 0.01, based on a chi-square goodness of fit test!

This seems like a good point to release the twelve texts that I have OCRed and cleaned to the public. I have uploaded them to GitHub as HTML files. In this I have been partly inspired by the work of Alex Gil, now my colleague at Columbia University.

You can read them for your own entertainment (Jocrisse-maître et Jocrisse-valet is my favorite), stage your own production of them (I’ll buy tickets!) or use them as data for your scientific investigations. I hope that you will also consider contributing to the repository, by checking for errors in the existing texts, adding new texts from the catalog, or converting them to a different format like TEI or Markdown.

If you do use them in your own studies, please don’t forget to cite me along the lines given below, or even to contact me to discuss co-authorship!

Grieve-Smith, Angus B. (2016). The Digital Parisian Stage Corpus. GitHub. https://github.com/grvsmth/theatredeparis

Sampling is a labor-saving device

Last month I wrote those words on a slide I was preparing to show to the American Association for Corpus Linguistics, as a part of a presentation of my Digital Parisian Stage Corpus. I was proud of having a truly representative sample of theatrical texts performed in Paris between 1800 and 1815, and thus finding a difference in the use of negation constructions that was not just large but statistically significant. I wanted to convey the importance of this.

I was thinking about Laplace finding the populations of districts “distributed evenly throughout the Empire,” and Student inventing his t-test to help workers at the Guinness plants determine the statistical significance of their results. Laplace was not after accuracy, he was going for speed. Student was similarly looking for the minimum amount of effort required to produce an acceptable level of accuracy. The whole point was to free resources up for the next task.

I attended one paper at the conference that gave p-values for all its variables, and they were all 0.000. After that talk, I told the student who presented that those values indicated he had oversampled, and he should have stopped collecting data much sooner. “That’s what my advisor said too,” he said, “but this way we’re likely to get statistical significance for other variables we might want to study.”

The student had a point, but it doesn’t seem very – well, “agile” is a word I’ve been hearing a lot lately. In any case, as the conference was wrapping up, it occurred to me that I might have several hours free – on my flight home and before – to work on my research.

My initial impulse was to keep doing what I’ve been doing for the past couple of years: clean up OCRed text and tag it for negation. Then it occurred to me that I really ought to take my own advice. I had achieved statistical significance. That meant it was time to move on!

I have started working on the next chunk of the nineteenth century, from 1816 through 1830. I have also been looking into other variables to examine. I’ve got some ideas, but I’m open to suggestions. Send them if you have them!

Printing differences and material issues in Google Books

I am looking forward to presenting my Digital Parisian Stage corpus and the exciting results I’ve gotten from it so far at the American Association for Corpus Linguistics at Iowa State in September. In the meantime I’m continuing to process texts, working towards a one percent sample from the Napoleonic period (Volume 1 of the Wicks catalog).

One of the plays in my sample is les Mœurs du jour, ou l’école des femmes, a comedy by Collin-Harleville (also known as Jean-François Collin d’Harleville). I ran the initial OCR on a PDF scanned for the Google Books project. For reasons that will become clear, I will refer to it by its Google Books ID, VyBaAAAAcAAJ. When I went to clean up the OCR text, I discovered that it was missing pages 2-6. I emailed the Google Books team about this, and got the following response:

google-books-material-issue

I’m guessing “a material issue” means that those pages were missing from the original paper copy, but I didn’t even bother emailing until the other day, since I found another copy in the Google Books database, with the ID kVwxUp_LPIoC.

Comparing the OCR text of VyBaAAAAcAAJ with the PDF of kVwxUp_LPIoC, I discovered some differences in spelling. For example, throughout the text, words that end in the old fashioned spelling -ois or -oit in VyBaAAAAcAAJ are spelled with the more modern -ais in kVwxUp_LPIoC. There is also a difference in the way “Madame” is abbreviated (“Mad.” vs. “M.me“) and in which accented letters preserve their accents when set in small caps, and differences in pagination. Here is the entirety of Act III, Scene X in each copy:

VyBaAAAAcAAJ

Act III, Scene X in copy VyBaAAAAcAAJ

Act III, Scene X in kVwxUp_LPIoC

Act III, Scene X in copy kVwxUp_LPIoC

My first impulse was to look at the front matter and see if the two copies were identified as different editions or different printings. Unfortunately, they were almost identical, with the most notable differences being that VyBaAAAAcAAJ has an œ ligature in the title, while kVwxUp_LPIoC is signed by the playwright and marked as being a personal gift from him to an unspecified recipient. Both copies give the exact same dates: the play was first performed on the 7th of Thermidor in year VIII and published in the same year (1800).

The Google Books metadata indicate that kVwxUp_LPIoC was digitized from the Lyon Public Library, while VyBaAAAAcAAJ came from the Public Library of the Netherlands. The other copies I have found in the Google Books database, OyL1oo2CqNIC from the National Library of Naples and dPRIAAAAcAAJ from Ghent University, appear to be the same printing as kVwxUp_LPIoC, as does the copy from the National Library of France.

Since the -ais and M.me spellings are closer to the forms used in France today, we might expect that kVwxUp_LPIoC and its cousins are from a newer printing. But in Act II, Scene XI I came across a difference that concerns negation, the variable that I have been studying for many years. The decadent Parisians Monsieur Basset and Madame de Verdie question whether marriage should be eternal. Our hero Formont replies that he has no reason not to remain with his wife forever. In VyBaAAAAcAAJ he says, “je n’ai pas de raisons,” while in kVwxUp_LPIoC he says “je n’ai point de raisons.”

Act III, Scene XI (page 75) in VyBaAAAAcAAJ

Act III, Scene XI (page 75) in VyBaAAAAcAAJ

Act III, Scene XI (page 78) in kVwxUp_LPIoC

Act III, Scene XI (page 78) in kVwxUp_LPIoC

In my dissertation study I found that the relative use of ne … point had already peaked by the nineteenth century, and was being overtaken by ne … pas. If this play fits the pattern, the use of the more conservative pattern in kVwxUp_LPIoC goes against the more innovative -ais and M.me spellings.

I am not an expert in French Revolutionary printing (if anyone knows a good reference or contact, please let me know!). My best guess is that kVwxUp_LPIoC is from a limited early run, some copies of which were given to the playwright to give away, while VyBaAAAAcAAJ and the other -ais/M.me/ne … point copies are from a larger, slightly later, printing.

In any case, it is clear that I should pick one copy and make it consistent with that. Since VyBaAAAAcAAJ is incomplete, I will try dPRIAAAAcAAJ. I will try to double-check all the spellings and wordings, but at the very least I will check all of the examples of negation against dPRIAAAAcAAJ as I annotate them.

Sampling and the digital humanities

I was pleased to have the opportunity to announce some progress on my Digital Parisian Stage project in a lightning talk at the kickoff event for New York City Digital Humanities Week on Tuesday. One theme that was expressed by several other digital humanists that day was the sheer volume of interesting stuff being produced daily, and collected in our archives.

The author and child, sampling the mists at Yaddo in 2003

The author with child, visiting Yaddo in 2003

I was particularly struck by Micki McGee’s story of how working on the Yaddo archive challenged her commitment to “horizontality” – flattening hierarchies, moving beyond the “greats” and finding valuable work and stories beyond the canon. The archive was simply too big for her to give everyone the treatment they deserved. She talked about using digital tools to overcome that size, but still was frustrated in the end.

At the KeystoneDH conference this summer I found out about the work of Franco Moretti, who similarly uses digital tools to analyze large corpora. Moretti’s methods seem very useful, but on Tuesday we saw that a lot of people were simply not satisfied with “distant reading”:

I am of the school that sees quantitative and qualitative methods as two ends of a continuum of tools, all of which are necessary for understanding the world. This is not even a humanities thing: from geologists with hammers to psychologists in clinics, all the sciences rely on close observation of small data sets.

My colleague in the NYU Computer Science Department, Adam Myers, uses the same approach to do natural language processing; I have worked with him on projects like this (PDF. We begin with a close reading of texts from the chosen corpus, then decide on a set of interesting patterns to annotate. As we annotate more and more texts, the patterns come into sharper focus, and eventually we use these annotations to train machine learning routines.

One question that arises with these methods is what to look at first. There is an assumption of uniformity in physics and chemistry, so that scientists can assume that one milliliter of ethyl alcohol will behave more or less like any other milliliter of ethyl alcohol under similar conditions. People are much less interchangeable, leading to problems like WEIRD bias in psychology. Groups of people and their conventions are even more complex, making it even more unlikely that the easiest texts or images to study are going to give us an accurate picture of the whole archive.

Fortunately, this is a solved problem. Pierre-Simon Laplace figured out in 1814 that he could get a reasonable estimate of the population of the French Empire by looking at a representative sample of its départements, and subsequent generations have improved on his sampling techniques.

We may not be able to analyze all the things, but if we study enough of them we may be able to get a good idea of what the rest are like. William Sealy “Student” Gosset developed his famous t-test precisely to avoid having to analyze all the things. His employers at the Guinness Brewery wanted to compare different strains of barley without testing every plant in the batch. The p-value told them whether they had sampled enough plants.

I share McGee’s appreciation of “horizontality” and looking beyond the greats, and in my Digital Parisian Stage corpus I achieved that horizontality with the methods developed by Laplace and Student. The creators of the FRANTEXT corpus chose its texts using the “principle of authority,” in essence just using the greats. For my corpus I built on the work of Charles Beaumont Wicks, taking a random sample from his list of all the plays performed in Paris between 1800 and 1815.

What I found was that characters in the randomly selected plays used a lot less of the conservative ne alone construction to negate sentences than characters in the FRANTEXT plays. This seems to be because the FRANTEXT plays focused mostly on aristocrats making long declamatory speeches, while the randomly selected plays also included characters who were servants, peasants, artisans and bourgeois, often in faster-moving dialogue. The characters from the lower classes tended to use much more of the ne … pas construction, while the aristocrats tended to use ne alone.

Student’s t-test tells me that the difference I found in the relative frequency of ne alone in just four plays was big enough that I could be confident of finding the same pattern in other plays. Even so, I plan to produce the full one percent sample (31 plays) so that I can test for differences that might be smaller

It’s important for me to point out here that this kind of analysis still requires a fairly close reading of the text. Someone might say that I just haven’t come up with the right regular expression or parser, but at this point I don’t know of any automatic tools that can reliably distinguish the negation phenomena that interest me. I find that to really get an accurate picture of what’s going on I have to not only read several lines before and after each instance of negation, but in fact the entire play. Sampling reduces the number of times I have to do that reading, to bring the overall workload down to a reasonable level.

Okay, you may be saying, but I want to analyze all the things! Even a random sample isn’t good enough. Well, if you don’t have the time or the money to analyze all the things, a random sample can make the case for analyzing everything. For example, I found several instances of the pas alone construction, which is now common but was rare in the early nineteenth century. I also turned up the script for a pantomime about the death of Captain Cook that gave the original Hawaiian characters a surprising (given what little I knew about these attitudes) level of intelligence and agency.

If either of those findings intrigued you and made you want to work on the project, or fund it, or hire me, that illustrates another use of sampling. (You should also email me.) Sampling gives us a place to start outside of the “greats,” where we can find interesting information that may inspire others to get involved.

One final note: the first step to getting a representative sample is to have a catalog. You won’t be able to generalize to all the things until you have a list of all the things. This is why my Digital Parisian Stage project owes so much to Beaumont Wicks. This “paper and ink” humanist spent his life creating a list of every play performed in Paris in the nineteenth century – the catalog that I sampled for my corpus.