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FYI, this course was very well received last year, and offers tools/methods of increasing relevance in this "big data" world.


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Analysis of Large-Scale Network Data, Ann Arbor, Michigan, June 18-22, 2012

Instructor:  Jukka-Pekka Onnela, Harvard University  

 

This year the ICPSR will be offering a special network analysis workshop of interest to scholars who want to analyze large scale networks.  This 5-day intensive workshop provides training on how to effectively handle and analyze large scale networks on datasets involving millions of people or data points.  It is a third-level course, and assumes that participants already have experience in the methodology of network analysis at about the level of the second networks course offered by the ICPSR Summer Program.

 

For information on this course and other network courses at ICPSR, along with fees and registration, visit the ICPSR Summer Program website http://www.icpsr.umich.edu/sumprog/


Full Course Description:  this workshop offers an introduction to computational network analysis. It is based on learning how to write scripts, or short snippets of code, using Python and NetworkX. This approach is extremely versatile, enabling one to analyze structural properties of networks, generate networks from microscopic rules, simulate dynamic processes on networks, and much more. The approach is also scalable, meaning that the methods may be applied to systems of various sizes, from small networks with a few actors to massive networks consisting of millions of nodes.

Participants will learn the necessary scripting skills, and the associated support skills, that will enable them to build their own tools for carrying out computational network analysis. The basics of Python and NetworkX will be taught (although this is not a course on programming) so that this powerful combination can be applied by participants to network analysis.

After the workshop, and a little practice, the participants will be able to run a large variety of analyses and simulations on networks. Some examples include examining network properties under a structural perturbation (e.g. node and/or tie removal); running epidemic spreading models (SIR, etc.) on networks; detecting network communities; simulating opinion formation models; generating networks from microscopic mechanisms; etc.

The workshop will include both lectures and hands-on computer laboratory exercises.


More information about the ICPSR Summer Program is available at http://www.icpsr.umich.edu/sumprog/

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