Vai al contenuto principale
Oggetto:
Oggetto:

Complex networks

Oggetto:

Complex networks

Oggetto:

Academic year 2024/2025

Course ID
ONC0256
Teacher
Rossano Gaeta (Lecturer)
Year
1st year
Teaching period
First semester
Type
Basic
Credits/Recognition
6
Course disciplinary sector (SSD)
INF/01 - informatics
Delivery
Formal authority
Language
English
Attendance
Obligatory
Type of examination
Written and oral (optional)
Prerequisites
A strong working knowledge of probability and linear algebra (at the
level of a bachelor degree in a scientific discipline) will certainly be helpful, as is some mathematical maturity. The ability to write code is important, because programming skills are required for the coursework project.
Oggetto:

Sommario del corso

Oggetto:

Course objectives

This module introduces the fundamental concepts, principles and methods in the interdisciplinary  field of network science, with a particular focus on analysis techniques, modeling, and applications for the World Wide Web and online social media. Topics covered include graphic structures of networks, mathematical models of networks, common networks topologies, structure of large scale graphs, community structures, epidemic spreading, PageRank and other centrality measures, dynamic processes in networks.

Oggetto:

Results of learning outcomes

- Knowledge and understanding

Students will learn how to define and calculate basic network graphic metrics, describe structural features of socio-technical networks, relate graphic properties to network functions and evolution, relate local properties to global emerging patterns, explore new angles to understand network collective behaviours.

 - Applying knowledge and understanding

Students will possess the ability to design and conduct analysis on large network datasets, visualize networks to highlight structural and global features, use network analysis tools, such as networkX library (Python). The knowledge will be sufficient for reading and understanding a scientific paper on topics coherent with the course contents.

- Making judgements

Students will be able to select the appropriate network metrics and structural properties to design and conduct analysis on large network datasets.

- Communication skills

Students will be able to discuss about networks analysis, to communicate the results of their findings, to summarize and discuss a scientific paper on topics coherent with the course contents.

Oggetto:

Program

  • Introduction to complex networks
  • Graph theory and network metrics
  • Centrality, small world, hubs
  • Directed, weighted and temporal networks
  • Strong and weak ties
  • Structural holes, bridges e graph partitions
  • Networks and homophily
  • Power laws and rich gets richer phenomena
  • Epidemics on graphs
  • Community detection
  • Hits and Page Rank algorithms
Oggetto:

Course delivery

A Moodle webpage is created for the course. All course materials, such as lecture notes and online resources will be shared. By using the Moodle, students will also be able to discuss ideas and questions with the lecturer and other students.

Students should have be previously authorized before accessing to moodle webpages. If you need assistance, please contact the instructors.

Oggetto:

Learning assessment methods

Practical project (30%): individual project on complex network analysis (programming in R or Python is required). 

Writing examination (70%): Questions/exercises on theory.

Oral examination (optional): according the instructor's guidelines that will be given during the course

Suggested readings and bibliography

Oggetto:

A First Course in Network Science
Authors: Filippo Menczer, Santo Fortunato, Clayton A. Davis
Publisher: Cambridge University Press
ISBN: 9781108653947
Url: https://www.cambridge.org/core/books/first-course-in-network-science/EE22722F27519D8BB1443C7225C57BAF 

Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press
Author: David Easley and Jon Kleinberg
Publisher: Cambridge University Press
ISBN: 9780521195331
Url: https://www.cs.cornell.edu/home/kleinber/networks-book/

 

**Additional Readings:**

  

Network Science
Author: Albert-László Barabási
Publisher: Cambridge University Press
ISBN: 9781107076266
Url: http://networksciencebook.com

Networks: an introduction
Author: Newman, Mark E. J.
Publisher: Oxford University Press
ISBN: 9780199206650

Complex Network Analysis in Python, Recognize → Construct → Visualize → Analyze → Interpret
Author: Dmitry Zinoviev
Edition: P1.0
Publisher: The Pragmatic Bookshelf
ISBN: 978-1-68050-269-5
Url: https://pragprog.com/book/dzcnapy/complex-network-analysis-in-python



Oggetto:

Notes

Timetable:

  • To be defined
  • To be defined

First lecture: To be defined

All the lectures will be held at a site to be defined

Enroll
  • Open
    Oggetto:
    Last update: 02/07/2024 10:24
    Non cliccare qui!