Workshop: Team Management
A.Y. 2024/2025
Learning objectives
The course aims to provide knowledge on utilizing network science and data analysis as tools for effective team management, enabling students to understand and optimize team dynamics, collaboration patterns, and organizational structures from a data science point of view.
Expected learning outcomes
Students will develop an understanding of fundamental social network analysis concepts, gain practical skills in analyzing team communication patterns, and learn to identify key organizational structures through network metrics.
Lesson period: Second semester
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Second semester
Course syllabus
- Introduction to the course
- Bipartite networks
- Density and degree
- Connected components
- Centrality
- Clustering coefficient & Transitivity
- Bridges
- Reciprocity
- Assortativity
- The nature of social structure: Milgrim, Granovetter and Dunbar theories
- Community detection
link per online:
https://itucph.zoom.us/j/69137603315
- Bipartite networks
- Density and degree
- Connected components
- Centrality
- Clustering coefficient & Transitivity
- Bridges
- Reciprocity
- Assortativity
- The nature of social structure: Milgrim, Granovetter and Dunbar theories
- Community detection
link per online:
https://itucph.zoom.us/j/69137603315
Prerequisites for admission
Suggested: Programming in Python.
Teaching methods
Educational activities in computer laboratory.
Teaching Resources
Slides of the lessons, posted after each class.
Reza Zafarani, Mohammad Ali Abbasi, Huan Liu. Social Media Mining: An Introduction. A Textbook by Cambridge University Press http://www.socialmediamining.info/
Reza Zafarani, Mohammad Ali Abbasi, Huan Liu. Social Media Mining: An Introduction. A Textbook by Cambridge University Press http://www.socialmediamining.info/
Assessment methods and Criteria
Group project on network analysis
Final evaluation will consist of an in-person oral examination where each project group will present their work. During the presentation, students must:
- Demonstrate their project outcomes
- Explain their collaboration process, including: Tools and platforms used for team coordination; Individual responsibilities and contributions; Areas of collective discussion and group decision-making
The examination will be graded on a pass/fail basis, with possible outcomes of either 'Approved' or 'Not Approved.'
Final evaluation will consist of an in-person oral examination where each project group will present their work. During the presentation, students must:
- Demonstrate their project outcomes
- Explain their collaboration process, including: Tools and platforms used for team coordination; Individual responsibilities and contributions; Areas of collective discussion and group decision-making
The examination will be graded on a pass/fail basis, with possible outcomes of either 'Approved' or 'Not Approved.'
- University credits: 3
Humanities workshops: 36 hours
Professor:
Galdeman Alessia