Social Network Analysis

In this course, we study the theory and the computational tools for the analysis of social and information networks which have been expanded and spread via the use of the Internet and of the smart mobile devices. The course material includes:
Introduction to Network Science: Basic definitions for networks, role of networks and applications’ examples, topology control and network creation/design.
Graph theory elements and review of basic definitions.
Structure and features of complex and social networks: random network models, small-world networks, scale-free networks, regular networks, random geometric graphs, etc.
Evolutionary computing: genetic algorithms, cognitive algorithms, parallel computing and heuristic methods of computing.
Applications in Telecommunications and Computer Science: topology control, routing and resource allocation, impact of network structure in information diffusion/opinion formation, influence of social networks in recommender systems, epidemic information models, cooperation and synchronization, influence of social networks in advertising systems.
In the laboratory section, emphasis will be placed on the collection of free/open data from social networks and their processing and statistical analysis, targeting at the study of the topology and features of several networks, at the localization of influential network nodes, at the community detection, at the study of information diffusion, at the social recommender methods and systems.