Digital content processing
Course objectives
The course aims to provide students with knowledge relating both the structure of the computers and the operating systems. It continues by providing theoretical and methodological knowledge for the collection, representation and analysis of heterogeneous data. The course concludes by introducing technological and innovative aspects represented by current computer networks.
Channel 1
MATTEO CINELLI
Lecturers' profile
Program - Frequency - Exams
Course program
Introduction to Complex Systems
Data and Privacy
Introduction to a language for data analysis (Python, R)
Models of Complex Networks (Random Networks, Small-World, Scale-Free)
Characterization of Complex Networks (Metrics)
Community Detection Algorithms
Homophily, Assortativity
Data collection
Opinion Dynamics (Bounded Confidence Model, Complex Contagion)
Visualization and Presentation of Complex Networks and Models
Prerequisites
No prerequisites
Books
- Newman, M. (2018). Networks. Oxford university press.
- Barrat, A., Barthelemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge university press.
- Network Science, A.L. Barabàsi http://networksciencebook.com
Frequency
Classes in person
Exam mode
Written exam
Bibliography
- Newman, M. (2018). Networks. Oxford university press.
- Barrat, A., Barthelemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge university press.
- Network Science, A.L. Barabàsi http://networksciencebook.com
Lesson mode
In person lessons
- Lesson code1049427
- Academic year2024/2025
- CourseEconomics and communication for management and innovation
- CurriculumEconomics and communication for management and innovation (Percorso valido anche fini del conseguimento del doppio titolo italo-russo o italo-rumeno)
- Year2nd year
- Semester1st semester
- SSDINF/01
- CFU9
- Subject areaAttività formative affini o integrative