Introduction to Social Network Analysis (using UCINET)
Dates: 11-13th January 2010
Duration: 3 days (10am — 4:30pm)
Level: Introductory (days 1-2) / Intermediate (day 3)
Course Fee: £525 (£375 for those from educational institutions)
CCSR offer 5 free places to research staff and students within the Faculty of Humanities at the University of Manchester.
Course Leader:
Mark Tranmer, Nick Crossley, Martin Everett, Elisa Bellotti
Course Requirements:
No prior knowledge of Social Network Analysis is assumed for the main part of the course that takes place on day 1, day 2, and the first half of day 3. Some prior knowledge of regression will be very helpful, but not essential, for the gentle introduction to statistical models for social networks in the second half of day 3. We stress that the emphasis of this course is on substantive concepts and hands-on practical work but some background theoretical material will be presented where necessary
Course Summary
This is an introductory course, covering the concepts, methods and data analysis techniques of social network analysis. The course begins with a general introduction to the distinct goals and perspectives of social network analysis, followed by a practical discussion of network data, covering issues of collection, validity, visualization, and mathematical/computer representation. We then take up the methods of detection and description of structural properties, such as centrality, cohesion, subgroups, etc. Finally, we consider how to frame and test network hypotheses. This is a hands on course largely based around the use of UCINET software, and will give participants experience of analyzing real social network data using the techniques covered in the workshop. Towards the end of the workshop, a gentle introduction to statistical models for social networks, such as p* models, is also given. No prior knowledge of social network analysis is assumed for this course.
Course Objectives
The course will:
1. Introduce the idea of Social Network Analysis
2. Explain how to describe and visualise networks using specialist software (UCINET)
3. Explain key concepts of Social Network Analysis (e.g. Cohesion, Brokerage).
4. Provide hands-on training to use software to investigate social network structure
5. Provide a gentle introduction to statistical models for social networks and the motivation for modelling networks
Target Audience
The course is aimed at researchers who have substantive questions of that involve the study of relations between units, such as relations between people, organisations or countries.
Preliminary Reading
David Knoke, Song Yang (2008) Social Network Analysis (2ND edition)
Scott J (2000) Social Network Analysis: A handbook. Sage.
Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj (2005)Exploratory Social Network Analysis with Pajek
M. A. J. van Duijn & J. K. Vermunt (2006) What Is Special about Social Network Analysis? Methodology 2006; Vol. 2(1):2–6
Robert Hanneman and Mark Riddle (2005) Introduction to social network methods www.faculty.ucr.edu/~hanneman/nettext
Social Network Analysis short course materials:
Introducing Social Network Analysis