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There are still a number of places left on the upcoming three courses on social network analysis at the Centre for Census and Survey Research (www.ccsr.ac.uk) led by staff from the Mitchell Centre (www.ccsr.ac.uk/mitchell) at the University of Manchester.
1. Introduction to Social Network Analysis Using UCINET and Netdraw
11-13th April 2011
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 and subgroups. 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. No prior knowledge of social network analysis is assumed for this course.
2. Advanced Methods for One Mode, Two Mode and Egonetworks
13-15th April 2011
We will cover advanced topics in centrality (Eg Bonacich power beta centrality), and cohesive subgroups (Eg advanced secondary analysis and techniques such as markov clustering) together with methods for blockmodelling using both structural and regular equivalence. We shall examine particular data types, e.g. valued data and two mode data, consider issues such as missing data and cover more advanced topics for ego networks, including structural holes and brokerage roles. In addition we shall look at the matrix algebra routine and show how users can use UCINET in a more sophisticated way to run analysis and data manipulations that are not in the standard menu.
3. Statistical Analysis of Social Networks
13-15th April 2011
We begin by looking at ERGMs (Exponential Random Graph Models) using the software package PNET and also statnet in R. This allows us to answer questions such as: Are there more triads in my network than I would expect by chance? And more complex questions involving attributes such as am I more likely to be friends with someone who is a similar age to me? The second half of the course is devoted to the examination of longitudinal data using the R version of the SIENA package. This looks at network formation over time and is an actor based model that allows for endogenous network effects (such as transitivity and popularity) as well actor attributes (such as homophily) to be included in the model.
For more information and to book please go to http://www.ccsr.ac.uk/courses/list/
University of Manchester
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