Computational Language Technologies for Medievalists Summer School

Computational Language Technologies for Medievalists Summer School

Zentrum für Informationsmodellierung (Karl-Franzens-Universität Graz)
Karl-Franzens-Universität Graz
Zentrum für Informationsmodellierung
Gefördert durch
University of Graz, European Research Council
Findet statt
In Präsenz
Vom - Bis
08.07.2024 - 12.07.2024
Franziska Decker, Zentrum für Informationsmodellierung, Karl-Franzens-Universität Graz

The University of Graz is hosting a summer school on Computational Language Technologies for Medievalists from 8th to 12th July 2024. This five-day program will equip participants with essential skills in Natural Language Processing (NLP) specifically tailored to the challenges of working with medieval languages.

Computational Language Technologies for Medievalists Summer School

Embark on a five-day journey hosted by the University of Graz:

Natural Language Processing (NLP) has emerged as a crucial skill in many Digital Humanities scenarios seeking to unlock the potential of language-based technologies. Due to the particularities of medieval languages (e.g. special characters, historical language levels, scarce training data) medieval studies put particular challenges to the standard NLP methods. In our Summer School, we aim to guide postgraduate and PhD level participants through the conceptual foundations of NLP, offering hands-on exercises tailored to empower medievalists in curating content and managing metadata. This will include training in topic modeling, text re-use, authorship attribution, stylometry and basic application of large language models. Discover how to optimize your time and efforts effectively while integrating new tools into your scholarly pursuits.

In preparation for the main curriculum, we offer pre-school learning materials specifically designed to support novice applicants. These materials will provide foundational knowledge and essential skills, ensuring that participants, regardless of their level of expertise, can fully engage with and benefit from the Summer School experience.

No prior advanced mathematics or computer science knowledge is mandatory. Possessing basic Python syntax knowledge and command line-based or interactive computing environment-based (Jupyter Notebook, Google Colab) script execution is, however, advantageous. We expect basic computer literacy from all participants.

How to Apply: To be considered for participation in this Summer School, please submit a one-page CV and a concise letter of interest (maximum one page) addressing the following:
- Why do you wish to attend this Summer School? Submissions describing a concrete use case you consider (data, research questions) will have preference. You will get the chance to present your research in a poster session.
- Share your academic background and research specialization.
- Sketch your technology skills in the above mentioned fields

This initiative is generously funded by the University of Graz, ZIM-ACDH and the ERC DiDip Project.

Kindly email your application material to didip[at] with the subject "Application for NLP Summer School". The deadline for applications is 15 March 2024. Applicants will be notified of acceptance by 15 April 2023.

Please find further information at


Preliminary programm:

Day 1: Introduction to NLP and Text Analysis

- Python programming course for novice participant (technical)
- Introduction to digital humanities projects and resources using NLP (DH scholar presentation)
- What is NLP? Taxonomy of NLP Methods? Why is it relevant to medieval studies? (Overview of NLP tasks and applications) (technical)
- Practical Exercises: Setup (Juptyer, Colab, packages) (technical)
- Evening lecture: Jean-Baptiste Camps and reception

Day 2: Topic Modeling

- Topic modeling: Discovering hidden themes and topics in large collections of texts (DH Scholar presentation)
- Different levels of text analysis and representation methods (tokenization, stemming, lemmatization, TF-IDF, embeddings) (technical)
- Hands-on session: Applying topic modeling to a corpus of medieval charters

Day 3: Named Entity Recognition

- Applications of NER in genealogical research, prosopography, and historical event analysis (DH scholar presentation)
- Named entity recognition (NER): Identifying and classifying people, places, organizations, and dates in text (technical)
- Hands-on session: Building a simple NER system and exploring relationship extraction (technical)

Day 4: Text Reuse and Authorship Analysis

- Exploring how authors often borrowed, adapted, and transformed existing texts, creating intertextual networks (DH Scholar presentation)
- Methods for identifying text reuse through techniques like stylometry, plagiarism detection (word usage patterns, sentence structure, n-grams, different similarity measurements) (technical)
- Hands-on session: Use stylometric tools to compare different medieval texts and assess the possibility of authorship attribution (technical)

Day 5: Future Directions (LLM)

- Introduction to advanced methods and their NLP applications (DH scholar presentation)
- Challenges of using NLP in historical research.
- Presentation of the participants’ projects (Poster session)
- Open discussion: Exploring potential applications of NLP in students’ specific research projects.

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