Germany, Berlin

Social Network Analysis Using Stata

when 13 December 2017 - 15 December 2017
language English
duration 1 week
fee EUR 896

The field of Social Network Analysis is one of the most rapidly growing fields of the social sciences. Social network analysis focuses on the relationships that exist between individuals (or other units of analysis) such as friendship, advice, trust, or trade relationships. As such, network analysis is concerned with the visualization and analysis of network structures, as well as with the importance of networks for individuals’ propensities to adopt different kinds of behaviors. Up until now, researchers wishing to implement this type of analysis have been force to use specialized software for network analysis. A new set of user written commands (developed by Thomas Grund, coauthor of the forthcoming Stata Press title “An Introduction to Social Network Analysis and Agent-Based Modeling Using Stata”) are however, now available for Stata. This workshop introduces the so-called nwcommands suite of over 90 Stata commands for social network analysis. The suite includes commands for importing, exporting, loading, saving, handling, manipulating, replacing, generating, visualizing, and animating networks. It also includes commands for measuring various properties of the networks and the individual nodes, for detecting network patterns and measuring the similarity of different networks, as well as advanced statistical techniques for network analysis including MR-QAP and ERGM.

Course leader

Thomas Grund, University College Dublin

Target group

The workshop provides an interdisciplinary venue for social scientists, mathematicians, computer scientists, ethnologists, epidemiologists, organizational theorists, and others to present current work in the area of social networks.

Course aim

In common with TStat’s workshop philosophy, each individual session, is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the workshop, theoretical sessions are reinforced by case study examples, in which the course tutor discusses current research issues, highlighting potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, course leaders are able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data.

At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed during the course.

Fee info

EUR 896: Students*: € 735.00

Academic: € 1225.00

Government /Nonprofi t: € 1513.00

Commercial: € 1800.00

*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.

All fees are subject to VAT (applied at the current Italian rate of 22%).

Please note that a non-refundable deposit of €100.00 for students and €200.00 for academic, Government/Nonprofit and commercial participants, is required to secure a place and is payable upon registration. The number of participants is limited to 15. Places will be allocated on a first come, first serve basis.

Course fees cover: i) teaching materials (copies of lecture slides, databases and Stata routines used during the workshop); ii) a temporary licence of Stata valid for 30 days from the beginning of the workshop.

In order to maximize the usefulness of this workshop, we recommend that participants bring their own laptops with them, in order to be able to actively participate in the empirical sessions.

Individuals interested in attending this workshop must return their completed registration forms either by email ( or by fax (+39 0864 206014) to TStat by the 25th of November 2017.