Workshops
Network Analysis for Humanists
Giovanni Pietro Vitali
This course is designed to introduce participants to the fundamental concepts of network analysis. It is structured into three main sections, progressively guiding learners from basic examples to practical application using Gephi, a network visualization tool.
Examples of Network Analysis – this section provides an introduction to network analysis through real-world examples. Participants will explore various types of data visualization applied to network structures.
Preparing Your Data – data preparation is a crucial step in network analysis. This part covers formatting data for visualization and ensuring its usability in network modeling.
Building Your Own Network – a hands-on tutorial on creating a network using Gephi. Participants will learn how to visualize and analyze network structures through the software.
Giovanni Pietro Vitali is Associate Professor in Cultural History and Digital Humanities at Versailles Saint-Quentin-en-Yvelines University – Paris-Saclay University. Previously he was Marie Curie Research Fellow at University College Cork in collaboration with the University of Reading and New York University. His MSCA project, Last Letters from the World Wars: Forming Italian Language, Identity and Memory in Texts of Conflict, dealt with a linguistic and thematic analysis of the last letters of people sentenced to death during the First and the Second World Wars. From 2014 to 2018, he worked in France as a lecturer of Italian Studies at the University of Lorraine and the University of Poitiers. In 2018 he became an associate researcher at University of Oxford where he is the Digital Humanities advisor of the Prismatic Translation project.
Using LLMs in Humanities Research via API
Valdis Saulespurēns & Anda Baklāne
In this workshop, participants will learn how to access large language models via API and utilize them for bulk data analysis using Python. Through practical examples, we will explore prompt engineering techniques for tasks such as concept mining and named entity recognition in textual data. Additionally, we will examine challenges associated with historical digitized texts, including optical character recognition (OCR) errors, which may affect compatibility with language models. Participants will gain insights into how these models can be leveraged for error correction and translation, enhancing the usability of imperfect textual data.
The workshop is designed for researchers, data analysts, and professionals in text analysis, digital humanities, and computational linguistics. Only a basic familiarity with Python is required, which can be gained by attending introductory workshops at the summer school or reviewing the provided preparatory materials.
Valdis Saulespurēns works as a researcher and developer at the National Library of Latvia. Additionally, he is a lecturer at Riga Technical University, where he teaches Python, JavaScript, and other computer science subjects. Valdis has a specialization in Machine Learning and Data Analysis, and he enjoys transforming disordered data into structured knowledge. With more than 30 years of programming experience, Valdis began his professional career by writing programs for quantum scientists at the University of California, Santa Barbara. Before moving into teaching, he developed software for a radio broadcast equipment manufacturer. Valdis holds a Master's degree in Computer Science from the University of Latvia. When not working or spending time with his family, Valdis enjoys biking and playing chess, sometimes even at the same time.
Anda Baklāne is a researcher and curator of digital research services at the National Library of Latvia. She teaches Introduction to Digital Humanities and Digital Social Sciences and Text Analysis and Visualization courses at the University of Latvia. Anda holds a master’s degree in philosophy and a PhD in literary theory. Her research interests include Latvian contemporary literature, metaphor, models, distant reading, and academic data visualization.
Digital Mapping for Humanists
Giovanni Pietro Vitali
This course is designed to introduce participants to the fundamental concepts of digital mapping for humanists. It is structured into three main sections, progressively guiding learners from basic IT skills to hands-on mapping using Carto, a web-based mapping platform.
Fundamental IT Skills – digital mapping requires a broad set of technical skills. This section covers the most commonly used programming languages, file formats, applications, and software necessary for working with digital maps.
Preparing Your Data – a crucial step in mapping is the creation and formatting of datasets. This section focuses on how to structure and organize data for use in mapping tools.
Building Your Own Map – a hands-on tutorial on creating custom maps using Carto. Participants will learn how to visualize spatial data effectively.
Carto platform: https://carto.com/
Giovanni Pietro Vitali is Associate Professor in Cultural History and Digital Humanities at Versailles Saint-Quentin-en-Yvelines University – Paris-Saclay University. Previously he was Marie Curie Research Fellow at University College Cork in collaboration with the University of Reading and New York University. His MSCA project, Last Letters from the World Wars: Forming Italian Language, Identity and Memory in Texts of Conflict, dealt with a linguistic and thematic analysis of the last letters of people sentenced to death during the First and the Second World Wars. From 2014 to 2018, he worked in France as a lecturer of Italian Studies at the University of Lorraine and the University of Poitiers. In 2018 he became an associate researcher at University of Oxford where he is the Digital Humanities advisor of the Prismatic Translation project.
Lectures
Large Language Models as Chainsaws: Fostering a Tool-critical Perspective on LLMs in DH Research
Tess Dejaeghere
This lecture will explore the challenges of applying NLP tools to digitally analyze literary-historical texts. We will examine the complexities of annotation, diverse modelling approaches ranging from rule-based to discriminative and generative systems, and the technical expertise required in DH to navigate the rapidly evolving NLP landscape. Next, we will discuss the rise of generative LLMs—their potential and limitations within digital humanities—and why they should be viewed and handled as powerful but indiscriminate tools, akin to chainsaws. A key focus will be a sneak peek of what the future of LLM-driven DH may look like, and the essential role of humanists in cultivating critical perspectives on AI. Finally, we will present case studies from our research center (Ghent Center for Digital Humanities), showcasing how we have utilized and assessed generative LLMs for information extraction tasks in literary-historical texts.
Tess Dejaeghere is a PhD-student affiliated with the Computational Literary Studies infrastructure (CLS infra) project and the Ghent Center for Digital Humanities (GhentCDH) at Ghent University. Her research caters to the application and evaluation of NLP-techniques for literary-historical texts, and fostering AI literacy and an AI-critical perspective in (digital) humanities.