Highlights
Tuition fee
500 EUR / full
500 EUR / full
Unknown
Tuition fee
500 EUR / full
500 EUR / full
Unknown
Duration
4 days
Duration
4 days
Apply date
Unknown
Apply date
Unknown
Start date
Unknown
Start date
Unknown
Campus location
Pisa, Italy
Campus location
Pisa, Italy
Taught in
English
Taught in
English

About

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.

Visit programme website for more information

Overview

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:

  • Foundations of NLP: Introduction to text preprocessing (tokenization, stemming, lemmatization), text representation models (Bag-of-Words, TF-IDF, word embeddings), and classification techniques.
  • 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.
  • 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.
  • 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.

    Programme Structure

    • Rise awareness on text analysis techniques
    • Understand/use (i) the text analysis/LLM terminology, (ii) the main sources of knowledge to update/specialize text analysis skills
    • Give a starting toolbox for working with text analysis
    • Demonstrate proficiency in a range of text analysis/LLM techniques
    • Navigate/implement different components of text analysis 
    • Start/improve participants text analysis research project
    • Apply the learned text analysis techniques
    • Matching the text analysis method & the research aim
    • Understand definition, functioning & potential applications of LLMs in innovation research & practice
    • Recognize the main limitations/risks of LLMs
    • Learn how to assess the performance of LLMs for innovation-related apps
    • Understand (i) who is doing what in our community, (ii) the historical evolution & significance of text mining & NLP in the context of innovation management, (iii) the current research landscape in Innovation community

    Audience

    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.

    Key information

    Duration

    • Full-time
      • 4 days

    Start dates & application deadlines

    Language

    English

    Credits

    3 ECTS

    Delivered

    On Campus

    Campus Location

    • Pisa, Italy

    What students do after studying Computer Science & IT

    This information is based on LinkedIn alumni data for graduates from 2018 to 2024 and may not fully represent all career outcomes

    Total alumni
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    Academic requirements

    We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

    English requirements

    We are not aware of any English requirements for this programme.

    Other requirements

    General requirements

    Admission RequirementsNo specific prerequisites are required for participation in the Summer School. However, candidates must hold at least a Bachelor’s degree or an equivalent qualification.Required documents

    • Identity Document (*PASSPORT in case you are a foreign student*)
    • Enrolment Form
    • Registration Form
    • Curriculum Vitae
    All the documents must be in pdf format, in order to upload them on the portal when required.IMPORTANT NOTICE:The maximum number of participants is set at 35. The first 15 eligible applications received will be admitted automatically (first come, first served). The remaining 20 places will be assigned based on the evaluation of the submitted documents. Priority will be given to candidates whose background, research interests, and motivations best align with the main theme of the Summer School, namely Natural Language Processing (NLP) and Innovation Research.

    Student Insurance via Studyportals Partner

    Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items like Additional medical costs, Repatriation, Liability etc. Make sure your student insurance covers your needs.

    Studyportals partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.

    Get your student insurance now

    Starting from €0.53/day, free cancellation any time.

    Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at University of Pisa and/or in Italy, please visit Student Insurance Portal.

    Tuition Fees

    Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.

    • International

      Non-residents
      500 EUR / full
      ≈ 500 EUR / full

    • Domestic

      Citizens or residents
      500 EUR / full
      ≈ 500 EUR / full

    Living costs

    Pisa

    Italy
    750 - 1100 EUR / month

    The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

    Funding

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