Programme

Students learn methodological elements of Social Network Analysis, combined with other analytical tools, such as Text Mining, applied to economic and business contexts. The study is not only theoretical but also focused on the practical application of these techniques through the use of specific software tools.

In the second part, the course focuses on acquiring managerial and strategic knowledge, including the study of leadership principles, team management, communication, problem-solving, and change management through the OCEAN method.

Below is a more detailed overview of the course content.

Part I: Business Analytics
- Introduction to Social Network Analysis and complex systems
- Network typologies and data collection
- Centrality measures
- Random networks, small-world and scale-free
- Clustering and structural holes
- Network communities
- Key roles in knowledge exchange networks
- Robustness and resilience
- Introduction to diffusion models
- Introduction to big data analytics
- Honest signals
- Semantic Brand Score

Part II: Business Management
- Problem solving (OCEAN method)
- Change management (OCEAN method)
- Leadership
- Teambuilding

Software:
- SBS BI, Pajek and Gephi.

Both modules include case studies and practical exercises.

The teacher provides a more detailed program on the Moodle platform.

Core Documentation

Fronzetti Colladon, A., & Vestrelli, R. (2025). Social Network Analysis and Text Mining for Big Data: The Power of Words and Networks. Routledge.

Fronzetti Colladon, A., & Grippa, F. (2025). Leading Meaningful Change. Edward Elgar.

All the materials made available by the teacher on the Moodle platform are part of the course, and their study is necessary to pass the final exam. They are provided in addition to the textbooks listed here.

Attendance

Students are strongly encouraged to attend classes, as in-class participation provides the opportunity to deepen their understanding through direct interaction with the instructor and classmates. Studying the materials provided and recommended by the instructor is important, as is attending lectures, which allows students to gain additional perspectives and information. For students who are unable to attend for valid reasons, as specified by the University regulations—such as working students—additional materials will be provided or recommended to facilitate the understanding of topics and ensure adequate exam preparation, allowing for remote learning. Students who fall under the categories outlined in the University regulations are invited to contact the instructor for further guidance.

Type of evaluation

Oral exam and project assessment (group work). Please refer to the Moodle platform for further details.

Programme

Students learn methodological elements of Social Network Analysis, combined with other analytical tools, such as Text Mining, applied to economic and business contexts. The study is not only theoretical but also focused on the practical application of these techniques through the use of specific software tools.

In the second part, the course focuses on acquiring managerial and strategic knowledge, including the study of leadership principles, team management, communication, problem-solving, and change management through the OCEAN method.

Below is a more detailed overview of the course content.

Part I: Business Analytics
- Introduction to Social Network Analysis and complex systems
- Network typologies and data collection
- Centrality measures
- Random networks, small-world and scale-free
- Clustering and structural holes
- Network communities
- Key roles in knowledge exchange networks
- Robustness and resilience
- Introduction to diffusion models
- Introduction to big data analytics
- Honest signals
- Semantic Brand Score

Part II: Business Management
- Problem solving (OCEAN method)
- Change management (OCEAN method)
- Leadership
- Teambuilding

Software:
- SBS BI, Pajek and Gephi.

Both modules include case studies and practical exercises.

The teacher provides a more detailed program on the Moodle platform.

Core Documentation

Fronzetti Colladon, A., & Vestrelli, R. (2025). Social Network Analysis and Text Mining for Big Data: The Power of Words and Networks. Routledge.

Fronzetti Colladon, A., & Grippa, F. (2025). Leading Meaningful Change. Edward Elgar.

All the materials made available by the teacher on the Moodle platform are part of the course, and their study is necessary to pass the final exam. They are provided in addition to the textbooks listed here.

Reference Bibliography

Other recommended books: - Brown, T. Change by Design, Revised and Updated. ‎Harper Business - Verganti, R. Overcrowded: Designing Meaningful Products in a World Awash with Ideas. The MIT Press.

Attendance

Students are strongly encouraged to attend classes, as in-class participation provides the opportunity to deepen their understanding through direct interaction with the instructor and classmates. Studying the materials provided and recommended by the instructor is important, as is attending lectures, which allows students to gain additional perspectives and information. For students who are unable to attend for valid reasons, as specified by the University regulations—such as working students—additional materials will be provided or recommended to facilitate the understanding of topics and ensure adequate exam preparation, allowing for remote learning. Students who fall under the categories outlined in the University regulations are invited to contact the instructor for further guidance.

Type of evaluation

Oral exam and project assessment (group work). Please refer to the Moodle platform for further details.