Program Overview

IQLA-GIAT Summer School in Quantitative Analysis of Textual Data

The international summer school IQLA-GIAT in Quantitative Analysis of Textual Data is an educational opportunity in the field of quantitative methods for text analysis. The school is aimed at undergraduate and graduate students, doctoral candidates, post-docs, researchers, and scholars from all disciplines within the humanities and social sciences who are interested in tools for studying large digital textual corpora.

Programme Overview

The programme of the summer school is characterized by three main elements:

1. A general part, which provides an introduction to quantitative methods for text analysis.
2. A thematic focus, which explores an emerging topic and its related effects on research.
3. A series of practical workshops, where participants can acquire practical skills in using advanced tools.

Theme and Focus

This year's theme addresses the challenges posed by artificial intelligence (AI) and the use of large language models (LLMs) to traditional methods of text data analysis. The central theme for the 2025 edition is the question: Large Language Models: Does AI Challenge Traditional Methods?

Objectives and Activities

The activities of the school are designed to stimulate critical reflection on the advantages and limitations of methods and to engage in discussions with participants in an interdisciplinary context about the potential, challenges, and opportunities of various approaches. The interdisciplinarity of the school is ensured both by the presence of speakers from different scientific fields and by the diverse backgrounds of the participants.

Key Information

• Dates: Monday, September 8th 2025 – Friday, September 12th 2025
• Target: Bachelor's, Master's and PhD students, post-doctoral researchers, scholars, and professionals
• Maximum Participants: 20
• Language: English
• Location: Padua

School Aims

The school aims to:

• Share knowledge about methods, software, corpora, scientific literature, and research results
• Promote dialogue between disciplines on a current topic such as the use of LLMs in text analysis
• Develop innovative analytical tools and integrated research methods
• Introduce young researchers to highly qualified research contexts
• Serve as an ideal platform for establishing collaborations in international research networks, developing cross-disciplinary skills, and exploring the new challenges of research in the fields of humanities and social sciences.