Academic Year 2019-2020
NETWORK SCIENCE
Teachers:
Massimo Franceschet
Massimo Franceschet
Total Course Credits: 6
Teaching Period: First Period
Teaching Language: Inglese
Prerequisites. Basic elements of statistics and linear algebra
Teaching Methods. The lessons will both theoretical and practical. The practical part is aimed at the acquisition of languages and software tools through case studies. They will use the following software tools: R with packages dplyr, ggplot2, igraph, ggraph.
Verification of Learning. The exam consists of a written, a project and an oral exam. The written part consists of open questions and exercises. The project must be carried out individually on a topic chosen by the student. The project must use methods, languages and software tools seen during the course (not necessarily all, but most) in an integrated and fluid way. The project must be documented in a report that describes the objectives, the analyzes and the results obtained. The oral exam concerns the discussion of the project of the student.
OBJECTIVES
* the student must have acquired the necessary knowledge to analyze a network in any domain
* the student must have learned at least one software for analysis and visualization of networks.
* the student must be able to interpret the experimental results and draw conclusions relevant to the domain of discourse
* the student must be able to communicate effectively the results of an experimental analysis
CONTENTS
The networks are ubiquitous in modern society, including social, technological, information, and biological networks. The course offers methods for analysis and visualization of network.
+ Introduction to R language
+ Introduction to data science, with a focus on analysis and visualization of structured data
+ Analysis and visualization of networks. The analysis will focus on the centrality and power measures, measures of similarity and diversity, community detection, structural properties of the network.
TEXTS
Mark Newman. Networks: An Introduction. Oxford University Press, 2010.Networks, crowds and markets.
David Easley and Jon Kleinberg. Cambridge University Press, 2010.
