Analysis of Large-Scale Networks


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.

Prerequisites: exposure to, and some experience with, the methodology of network analysis.

Fee: Members = $1500; Non-members = $3000

Tags: networks, computation, Network Analysis, large data sets, large-scale

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