The SIG-DLS Tool Inventory

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Let’s create our inventory of Digital Literary Stylistics methods and tools!

This summer at DH2018, the members of SIG-DLS in situ came up with some new activities for the new season. Among these was a DLS Tool Inventory of our own, reflecting our practice, with tested and tried methods, software, tools.

Just a spreadsheet… Will it become magic?


Well, here we are: happy to share with you all a spreadsheet that will hopefully become truly awesome. Let’s create the magic together!

Please go ahead and enter the tool/method that you know well in a one-line report. Mind you, that shall be tools/methods that are real and recent, tested and tried within the last five years. Please don’t enter reports on tools created by yourself. Where possible, your one-line report shall also include a brief and constructive report on strengths and weaknesses of the tool/version that you used; on usability with regard to your research question.


Computer Assisted Text Markup and Analysis (CATMA) – An undogmatic approach to corpus analysis and Germany’s literary super heroes

Do you know CATMA? Not yet? Then read the following blog. Do you think you know CATMA? It’s still a good idea to read the following blog…

CATMA is a web-application for text markup and analysis. Its central function is annotating, analyzing and visualizing one or multiple texts. CATMA has been around since 2008.

When the implementation of the web-application CATMA started in 2008, the focus was to create a tool for digital close reading. Although there always has been the possibility to run some standard queries as e.g. word frequencies automatically, the focus of the application was entirely on the annotation functionality of single texts. Ten years later, CATMA provides the possibility to store, manage and analyse not only single texts, but also bigger corpora – using both close and distant reading methods. Although CATMA still can be used for manual annotation of single texts, in this article, we want to show you how the web-application can be used on corpora.

Goethe and Schiller, Germany’s literary super heroes

Let’s say you would like to explore the authorial styles of Germany’s literary super heroes, Goethe and Schiller. As you want to make the two author corpora comparable, you choose 12 dramatic and 5 prosaic texts of each author. Just upload those texts to CATMA and organise them into different corpora, one with texts by Goethe and one with texts by Schiller. Once your corpora have been created in CATMA, you can easily export them, or, more important, share them with your team.

Without any further preparation you can now start analysing your corpora. Using the Analyze modul you can generate a word list with frequencies. This list will show you that there are around 800.837 words in your selection of Goethe’s texts with around 46.840 types. Schiller’s texts contain 35.351 word types and a total of 498.790 words. These numbers are not very meaningful yet, because, obviously, the texts do not have the same length. Looking at the word frequency list, from a narrative perspective, the first person pronoun “ich” (I) is probably most interesting as it points to a predominant first-person perspective. Or is it just the dramatic characters? Other highly frequent (but narratologically possibly less relevant) words in the Goethe corpus are “und” (and), “die” (the/who/which – female), “zu” (to), and “der” (the/who/which – male), much as in the Schiller corpus (albeit in the order “der”, “und”, and “die”). At this top tier of frequency, there seems to be a similarity.

Word frequencies in Goethe’s and Schiller’s texts

But how about the other end of the lexical spectrum? Goethe is known to have had a comparably large vocabulary, so we may quickly check the least frequent words in the corpus – those which are used only once. Are there many of these hapax legomena?

In the Goethe corpus they sum up to 28.792 words altogether. Schiller uses 21.025 words only once in the entire corpus. This means that Goethe uses 61.4% of all the types of this corpus only once. Schiller uses 59.4% of all types in the corpus only once. Maybe this similarity suggests that Schiller after all was closely following Goethe in variability of word use. However, nobody will ever know how large the vocabulary of Schiller’s works might have become had he reached the same old age as Goethe in the end…

If we turn away from the low frequencies now and have another look at the high ones, we get hold of another interesting phenomenon. Among the most frequently used signs by Schiller are question- and exclamation marks. They appear at ranks 4 (exclamation mark) and 8 (question mark). In the Goethe corpus they only make it to ranks 11 (exclamation mark) and 27 (question mark). A look at the distribution of exclamation and question marks in our corpora shows that the distribution of exclamation marks ist always higher than the one of question marks in the Goethe corpus. Schiller on the other side has written five texts in which there are more question marks than exclamation marks. Is it maybe that Schiller’s authorial signature is characterized by an unusual amount of questions? Especially his play “Don Carlos. Infant von Spanien” is characterized by question marks, as you can see in the CATMA small multiples view below:

Small multiples view of distributions of question- and exclamation marks in the works of Schiller

Our case study so far has applied some handy distant reading functions, which are often used in one way or another in stylistics. But CATMA offers also a method for what we call scalable reading. Starting off with distant reading as we did, you may now scale down a bit: Simple double clicking on one point in the distribution graph or one keyword in the keyword in context table will take you to the specific position in the text where you find either the keyword or the accumulation of a word or tag you found in your small multiple distribution graphs. So, you can go from corpus to multiple texts in one visualization, on to single text view and even to the very position at which you find one word in one text – changing dynamically from distant to close reading and back just as you wish. This scalability also allows to develop different kinds of interpretation from data analysis to more context-oriented interpretation of certain passages in single texts.

I leave you here to start your own case study now, be it on the style of Goethe and Schiller or other literary phenomena. But just before you do that, do know that there are more functions for working on corpora in CATMA, among which are automatic annotations of part of speech (POS) tagging, as well as that of verbal tense and temporal signals (in German texts).

And of course you can also use the central CATMA function, which is annotating one text, or a whole corpus, with your very own categories, analyzing and visualizing them. CATMA ist running as version 5.0 right now, but in 2019, CATMA 6.0 will be launched. Users can look forward to the new design of the graphical user interface, the optimization of workflows and the addition of some features. 

As we focused on the corpus-specific functions in CATMA in this article, you might want to have a look at our tutorials for a complete overview of the application’s functionalities: http://catma.de/documentation/tutorials/

Have fun annotating, exploring, and scaling!