Text Analysis and Large Language Models for Innovation Management

Language: English

Period: 1 – 4 September 2026

Deadline: 26 June 2026

Program Intensity: Full-time

ECTS: 3

Tuition fees: 500€

The Summer School “Text Analysis and Large Language Models for Innovation” offers an intensive four-day learning experience at the intersection of Natural Language Processing (NLP), Large Language Models (LLMs) and Innovation.

The program is designed for PhD students, researchers, and scholars in Innovation, Strategy Management, Management and Business, who wish to explore how text analysis can transform the way we analyse and interpret textual data from documents such as patents, scientific publications, and product reviews. Given the widespread use of LLMs across research fields and business contexts—and the sometimes uncritical way these systems are adopted—it is today fundamental to understand what these systems are, their main functions, and the alternative methods that can be used to achieve similar results in more efficient and effective ways. Equally important is the ability to assess the validity and reliability of these methods, and to recognize their potential applications in innovation research and practice. Without this awareness, there is a risk of relying on unreliable results and losing control over how we use these tools in research and decision-making.

Participants will gain both conceptual knowledge and hands-on skills through lectures, interactive sessions, and project work. The school combines methodological foundations with practical applications, ensuring participants leave with a strong toolbox for applying NLP techniques in their own research.

The main topics of the summer school are:

1. Foundations of NLP: Introduction to text preprocessing (tokenization, stemming, lemmatization), text representation models (Bag-of-Words, TF-IDF, word embeddings), and classification techniques.
2. NLP Techniques for Innovation Research: Focus on practical applications such as sentiment analysis, topic modelling, named entity recognition, and annotation. Participants will work in teams to apply these techniques to real-world datasets, including patents and scientific papers.
3. Validity, Reliability, and Trust in NLP for Innovation Research and Business: how NLP techniques are evaluated and used in both research and business contexts. Participants will explore the concepts of validity and reliability, learning how to assess whether NLP methods provide results that are accurate, consistent, and meaningful for innovation research. The program will also address how different methods can be compared, highlighting the trade-offs between accuracy, efficiency, and interpretability. A special focus will be given to the issue of trust in NLP systems in business, examining risks such as bias, misuse, and overreliance, and discussing strategies for ensuring responsible adoption.
4. Integration and Application: Project presentations, and expert talks on real-world NLP applications in innovation management. A special ‘Meet the Editors’ session will give participants the opportunity to interact directly with editors from leading journals in innovation management, gaining valuable insights into research trends, publication strategies, and the qualities that make a paper stand out.

Part of the Summer School will be dedicated to project work. Participants will collaborate in teams to prepare and develop a project, which they will present to the committee at the end of the program. This project will be considered as an exam. Accordingly, students will receive official recognition of the Summer School’s workload through a certificate of attendance, equivalent to 3 ECTS credits.

The Summer School will be activated with at least 15 students. The maximum number of participants is set to 35 students.

The Summer School will be held on campus in Pisa, at Centro Congressi Le Benedettine, Piazza San Paolo a Ripa D’Arno, 16.