Social Network Analysis 2017

Course Description

This course covers the basics of social network analysis. We start with an overview of concepts used to describe and measure networks. Next, we will discuss a series of models of how networks impact behavior, including contagion, diffusion, and opinion formation.

Course topics

1. Introduction to social network analysis
2. Network structure
3. Mathematical models of networks
4. Network centrality
5. Network communities
6. ‘Small-World’ Networks
7. Epidemics and information spreading in networks
8. Opinion formation and segregation in networks

Course tools

Gephi, Python, igraph


Basic statistics and linear algebra. Programming skills.


Mr. Ievgen Terpil
Data Scientists at YouScan / PhD student at Institute for Applied System Analysis

Affiliation: YouScan / Institute for Applied System Analysis, Kyiv, Ukraine

Currently I work as a Data Scientists at YouScan. Our company is focused on the analysis of social media and we constantly have a lot of text classification and text clusterization tasks.

I am also a graduate student at ESC “Institute for Applied System Analysis” of NTUU “KPI” now. My PhD thesis are focused on social networks analysis and public opinion modeling.

Fields of interests: Social Network Analysis, NLP, Deep Learning, Public opinion modeling.