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## NETWORK ANALYSIS

CODE 90530 2021/2022 6 cfu during the 1st year of 10852 COMPUTER SCIENCE (LM-18) - GENOVA 6 cfu during the 2nd year of 9011 MATEMATICA(LM-40) - GENOVA INF/01 English GENOVA 2° Semester AULAWEB

## AIMS AND CONTENT

### LEARNING OUTCOMES

Learning algorithms and techniques for large scale graph analytics, including centrality measures, connected components, graph clustering, graph properties for random, small-world, and scale free graphs, graph metrics for robustness and resiliency, and graph algorithms for reference problems.

### AIMS AND LEARNING OUTCOMES

At the end of the course, diligent students who have worked as instructed will have:

• acquired a basic understanding of some universal properties of graphs that can be used to study large networks, regardless of the application domain
• acquired a basic understanding of the evolution of large networks in the presence of failures or contagions
• learned some important ranking algorithms on graphs
• consolidated the theoretical knowledge of the topics seen during lectures, thanks to a series of exercises that will allow them to put into practice the theory seen in class

### PREREQUISITES

To be successful in this course, students should have basic knowledge concerning:

• programming (for the practical activities)
• web (how it works, its structure)

### TEACHING METHODS

Lectures, practicals, and individual study.

### SYLLABUS/CONTENT

• Background on linear algebra and probability.
• Complex networks introduction: examples from biology, sociology, economy, computer science.
• Network topology (global and local level): connectivity, clustering, centrality measures, diameter, cliques, communities.
• Graph models: random graphs, small-world, scale-free networks.
• Graphs robustness and fault tolerance.
• Web graph: Markov chains and random walk, ranking, search engines.
• Dynamic evolution of graphs.
• Epidemic models.
• Case study: web, social media, epidemic models.
• Complex data visualization using open source software tools.

## TEACHERS AND EXAM BOARD

### Exam Board

MARINA RIBAUDO (President)

MATTEO DELL'AMICO

GIOVANNA GUERRINI (Substitute)

## LESSONS

### Class schedule

All class schedules are posted on the EasyAcademy portal.

## EXAMS

### EXAM DESCRIPTION

Oral examination with discussion of the practicals assigned during the course.

### ASSESSMENT METHODS

Individual interview.

### Exam schedule

Date Time Location Type Notes
07/01/2022 09:00 GENOVA Esame su appuntamento
08/06/2022 09:00 GENOVA Esame su appuntamento
22/07/2022 09:00 GENOVA Esame su appuntamento
08/09/2022 09:00 GENOVA Esame su appuntamento
16/09/2022 09:00 GENOVA Esame su appuntamento
10/02/2023 09:00 GENOVA Esame su appuntamento