The Dragonfly's Gaze Blog

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The Schiller-Kleist Uncertainty Principle (guest post)

This is a guest post, written by Philip Dürholt, a student in the “Digital Humanities” program (BA and MA) at the Department for Literary Computing, University of Würzburg. As always, comments are welcome! I’m a student at the University of Würzburg. My subjects are Philosophy and Digital Humanities. Last winter semester I had an interesting mix of courses: Quantitative Analysis...

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How to Create Lemmatized (French) Text for Topic Modeling

It would not, some years ago, have occurred to me that anyone would want to reduce literary texts to the following pitiful state: “me avoir tu faire un rapport bien sincère / ne déguiser tu rien de ce que avoir dire mon père / tout mon sens à moi-même en être encor charmer : / il estimer Rodrigue autant que...

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Extracting selected text from XML files using lxml in Python

As you can probably guess from the title, this post is a companion piece to another recent post dealing with the creation of simple TEI from HTML in Python (actually, using Python as a wrapper to several Regular Expressions). Once you have created such TEI files, have annotated them more richly by hand or by some other means, or were...

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Of the Digital Humanities considered as a Jazz ensemble

We frequently speak of Digital Humanities projects – in which people from one or several disciplines such as literary studies, musicology and/or art history work together with colleagues from computer science and/or statistics – using concepts like inter- or transdisciplinarity or like collaboration.[1] The danger, we quickly notice, lies in the “divison of labor” such arrangements imply. Such division of...

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Enrichment by Elimination, or: How to turn HTML into simple TEI using Python

There are lots of full text repositories of literary works out there, be it the venerable Project Gutenberg (founded in 1971, when the internet was just a few dozen computers), a pioneer like Gallica (with increasing amounts of plain text in the 90-95% correct OCR range), or a crowdsourced efforts like Wikisource (with nifty quality indicators). Closer to my geographical...

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Big? Smart? Clean? Messy? Data in the Humanities

(Please note that a revised version of this post has been published in the Journal for Digital Humanities in december 2013. – The original post is a slightly edited version of a talk I gave at the European Summer School “Culture & Technology at the University of Leipzig, Germany, on July 26 2013.) This talk is about data in the...

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My DH2013 program, possibly

The Digital Humanities Conference 2013 in Lincoln, Nebraska will start very soon. The program is packed with long and short talks and panel sessions in six parallel tracks, and of course the whole breadth of DH is represented. But computational text analysis seems to be one of the major topics again, after it was so prominent last year at DH2012...

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What the perfect repository for text analysis looks like (to me)

The longer I work with various collections of literary texts, available in various formats, and for use with various tools, the more I would like to have a nice repository which me and others could use to ingest, store, transform, update and extract text collections. So what would this repository look like? Basically, I’m describing a use case, and would...

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Annotation, or: it doesn’t always have to be quantitative analysis

Up to now – and this means for its first year, my first post here dating from 12 months ago – this blog has been primarily concerned, with respect to text analysis, with quantitative approaches. However, this is of course only one part of computational text analysis, and computationally supported manual annotation of texts is another one. This is what...

Fig. 2: "Communities" based on modularity analysis in part of 223 plays 0

Getting a closer look: More on visualizing results from stylometry with Gephi

This post is a follow-up post to my last brief post on the new version of the stylo script and its output for visualization with Gephi. Today, I just want to report on what Maciej told me about the technical details, and to show some more graphs resulting from my data. First things first, then. Here is how the data for...

Fig. 2: View just of the nodes without edges, for 223 plays. (License: CC-BY-SA 3.0) 1

Connecting our Tools, or: Stylometry and Network Analysis made easy

Do you like stylometry, and maybe have tried out the scripts for R provided by the Computational Stylistics Group? And do you like visualisation, and maybe have played around a bit with Gephi, the network visualisation tool? I suppose it’s rather likely that you have, as a reader of this blog, or at least that your interested in this kind...

Image by user IllonkaTallina on Flickr, published under a Creative-Commons BY-SA-NC license. http://www.flickr.com/photos/92641139@N03/8423301722/ 2

Catching up: “Statistics: Making Sense of Data” on Coursera

When you’re trying to figure out how best to use all these wonderful tools we now have for the computational analysis of literary texts (such as the stylometry scripts, MALLET, WEKA, and many more), you tend to get into situations where you wish your knowledge in statistics was more solid, recent, broad, and thorough. (I did study psychology as a...

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Enhancement, Transformation, and Zukunftsmusik: Established methods of interpretation transposed into the computational realm.

One of my favorite literary genres is French twentieth-century crime fiction, roughly from the 1930s (Georges Simenon) via the 1950s (Léo Malet) to the 1970s (Jean-Patrick Manchette). This is quite a large area, so one of the things I would like to do, if the state of text digitization and copyright law will permit it some day, is to do...

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Busy times, and some light at the horizon

Lot’s of things have been going on over these last weeks. Some of them were related to text analysis, others were rather related to job interviews, grant writing, teaching, real work, and travel, and I was just too busy to write anything here. Instead of a “real” post, this is just a way for me to cover the ground and...