Introduction to Social Network Analysis

Course details

statistics course | level: intermediate
registrations and venue via 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.

Fee:
PhD students and post-doctoral fellows: € 150*
Academics: € 250
Public and private sector: € 500

*Note for UGent doctoral students: the course has been submitted for recognition to the UGent Doctoral Schools. Subject to approval, they can apply for reimbursement through an application of recognition with the UGent Doctoral Schools. Doctoral students from other Flemish universities can be reimbursed by FLAMES upon complete attendance. Payment conditions: The registration fee is due within 30 days following receipt of the invoice. Payment is possible through bank transfer with clear statement of the structured message on the invoice. Cash payments are not possible.

Payment conditions:
The registration fee is due within 30 days following receipt of the invoice. Payment is possible through bank transfer with clear statement of the structured message on the invoice. Cash payments are not possible.

Cancellation by the participant:
You are registered for the course from the moment the standardized confirmation mail is sent to you by FLAMES-UGent. From that moment on the cancellation and payment conditions are in effect.

Venue:
UGent - Campus Sterre - Building S9
PC room 3.1 Konrad Zuse (3rd floor)
Krijgslaan 281, 9000 Gent

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

Instructor

Dr. Jef Vlegels