Summer School: Text Mining for Innovation Management

Dates: 13-14 June 2024

Location: Stockholm, Sweden


This summer school is designed for PhD students, researchers  and scholars in the field of Innovation Management who are interested in harnessing the power of Text Mining (TM) and Large Language Models (LLMs). Over two engaging days, participants will be introduced to a wide range of Text Mining techniques and how these can be applied in the context of innovation management. 

The summer school commences with a comprehensive introduction to the realm of Text Mining and its evolution, providing historical context and setting the stage for subsequent, more in-depth modules. 

Over the course of the program, participants will gain proficiency in a variety of techniques including document retrieval, Natural Language Processing (NLP), data visualization, and more applied to patents, scientific publications and other science and technological documents. Participants will explore several key elements of NLP, such as Bag-of-Words (BoW) models, word embeddings, and text analysis at both document and word levels. 

Participants will have the opportunity to familiarize themselves with the cutting-edge ChatGPT through an interactive session titled “The Prompt Canva®: Learn How to Interact with ChatGPT”. 

The program is highly interactive, with a two day datathon  parallel to all of the lecture, to put in practice from day zero what students have learned. Participants will apply their learned skills on real-world datasets related to Innovation Management, leading to a final presentation of results. A dedicated section also explores the significant contributions, journals, and authors in Innovation Management, culminating in the creation of a shared research agenda.  

This summer school is more than just a learning experience; it’s a platform for fostering collaboration, innovation, and a deeper understanding of the exiting and growing field of TM in the context of innovation management. 

Learning Outcomes

Rise awareness on text mining (TM) techniques

  • Understand and be able to use the TM terminology
  • Understand the main sources of knowledge to update and specialize TM skills

Give a starting toolbox for working with TM

  • Demonstrate proficiency in a range of text mining and Natural Language Processing techniques
  • Navigate and implement different components of NLP such as Bag-of-Words (BoW) models, word embeddings, and text analysis at both document and word levels
  • Operate and interact effectively with large language models such as ChatGPT using prompt engineering

Start or Improve participants TM research project

  • Apply the learned text mining techniques to participants’ research project
  • Matching the TA method and the research aim

Understand who is doing what in our community

  • Understand the historical evolution and significance of text mining and NLP in the context of innovation management

Audience and registration

The summer school on Text Mining for Innovation Management is open to PhD Students, researchers and scholars in the innovation management community interested in the topic. 

All the interested people can apply for participation filling the following form. 

Deadline for application: 31/03/2024.

Please note that there are no mandatory prerequisites. The only requirement is a keen interest in TM and its applications in innovation management. If you are enthusiastic about learning and applying TM techniques in your research, this summer school will be a valuable and rewarding experience.


Department of Engineering Design, KTH Royal Institute of Technology. Brinellvägen 85, SE-114 28 Stockholm, Sweden


  • No fees for partecipants! Applications received through Google Form will be evaluated in order to reach a maximum number of 25 participants. The priority will be given to those who register first.
  • Cofee breaks and dinner of the second day offered by the organisation.  

project work and certificate of attendance

Part of the summer school will be dedicated to a project work. Participants will have time to prepare a work in teams, which they will present at our committee at the end of the school. We will consider this work as an exam, therefore, we will recognize the hours of the summer school (20) for doctoral students with a certificate, counting as 2 EC.


  • Filippo Chiarello, PhD, Ass. Professor of Natural Language Processing and Design (University of Pisa)
  • Mats Engwall, PhD, Professor of Industrial Management, KTH
  • Mats Magnusson, PhD, Professor of Product Innovation Engineering, KTH
  • Vito Giordano, PhD, Researcher in Natural Language Processing and Innovation (University of Pisa)
  • Ivan Zupic, PhD, Lecturer in Lecturer in Entrepreneurship (University of London)


Ass. Prof. Filippo Chiarello, PhD:




Day 1 

Time Module Topic Description Duration (mins)
9:00 – 9:15 Introduction Presentation of the school & participants. Brief introduction of the summer school and participants. 15
9:15 – 9:45 Introduction The story of TM and NLP Overview of the history and evolution of TM and NLP 30
9:45 – 10:30 Introduction Datathon: Team creation & Definition of the RQs Teams are formed and research questions are defined for the Datathon 45
10:30 Coffee Break 30
11:00 – 12:00 Document Retrieval Search Strategy Develop an effective strategy for finding documents 60
12:00 – 12:30 Document Retrieval Web scraping & APIs Learn how to extract information from websites programmatically and understand how to use APIs to retrieve data 30
12:30 – 13:00 Document Retrieval Datathon: Query Design 30
13:00 – 14:00 Lunch Break 60
14:00 – 15:00 Natural Language Processing Tokenisation, Normalisation, POS Delve into, a fundamental part of BOW model. 60
15:00 – 16:00 Natural Language Processing Embeddings: W2V, BERT and GPT Introduction to Word2Vec, a popular word embedding technique. 60
16:00 – 16:30 Coffee Break 30
16:30 – 17:30 Natural Language Processing The prompt canva ®:  learn how to interact with chatGPT This interactive session introduces participants to the concept of prompt engineering, a key aspect of effective communication with the GPT models, including ChatGPT. 60
17:30 – 19:30 Natural Language Processing Datathon: Natural Language Processing 120
20:00  Dinner    


Day 2

Time Module Topic Description Duration (mins)
9:00 – 10:00 Text Analysis Document Classification & Sentiment Analysis Learn about techniques for classifying documents. Overview of sentiment analysis techniques. 60
10:00 – 11:00 Text Analysis Topic Modelling & Bert-topic Introduction to the concept of topic modelling. 60
11:00 – 11:30 Coffee Break 30
11:30 – 13:00 Working on projects Participants will have time to work on the group project 90
13:00 – 14:00 Lunch Break 60
14:00 – 15:30 Text Analysis Meet the editors The participants will have the opportunity to interact with the editors of … to discuss about their research project. 90
15:30 – 16:00 Coffee Break 30
16:00 – 16:30 TM for Innovation Management Relevant contributions in Innovation Management Overview of significant contributions in Innovation Management. 30
16:30 – 17:00 TM for Innovation Management Relevant Journals & authors Discussion on key journals and authors in Innovation Management. 30
17:00 – 18:00 TM for Innovation Management Research Agenda Setting up a research agenda for Text Mining in Innovation Management 60
 18:00 – 20:00 TM for Innovation Management Datathon: Working on projects. 120
20:00-21:00 Pizza!!!


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