Introduction to Social Network Analysis (SNA)

Introduction to Social Network Analysis (SNA)

  • 19/04/2021 - 22/04/2021
    1:00 pm - 5:00 pm

Course details

statistics course | level: intermediate | register now
for questions related to this event, contact ugent@flames-statistics.com
affiliation: Ghent University


Abstract

This is an introductory course in Social Network Analysis. It is a practical introduction to the main concepts, methods and data analysis techniques of SNA.
The course will start with an introduction to the distinct goals and perspectives of SNA. Next, we will give a practical introduction to network data structures in which we will cover specific issues in data collection, visualization and computer representation. The course then focuses on how to uncover structural properties of networks (e.g. clustering, hierarchy, density) and identifying different roles in a network (e.g. individual centrality measures, clique membership, structural equivalence). Finally, we will give a short and basic introduction to inference for network structures and attributes using exponential random graph models (ERGMs) and stochastic actor-oriented models (Siena). Throughout the course, some pivotal SNA theories will be explained, but the main focus is practical.

All analysis will be done in R statistical software.

Course objective: a good understanding of the basic SNA concepts, possibilities and data properties. After following the course students should be able to design a SNA study, do some first analysis and interpret results.

For whom:
(PhD) students, postdocs and researchers in other institutions interested in Social Network Analysis (SNA). It’s a methodological course in which we’ll use empirical examples from a wide range of disciplines. But typically SNA is applied by researchers from social sciences, life sciences, psychological and pedagogical sciences, economical sciences and health sciences.


Prerequisites

Understanding of basic inferential statistics: hypothesis testing (e.g. t-tests), p-values, statistical significance.

Basic skills in R (vectors, indexing, functions, ...). It is recommended for the students to have followed an R intro, e.g. the Flames introduction to R course

Students who are uncertain about their level of preparation are encouraged to contact the instructor.


Background readings


Fee

PhDs and postdocs of a Flemish university: free
Other academics: 120 €
Non-profit/Social sector: 200 €
Private sector: 400 €


Venue

Ghent University


Instructor

Jef Vlegels


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