hw1 - CS224W - Social and Information Network Analysis Fall...

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CS224W - Social and Information Network Analysis Fall 2010 Assignment 1 Due 11:59pm October 14, 2010 General Instructions You are required to write the name of your collaborators for this assignment on your solution report. You are also required to submit the source code used to obtain your solutions along with your report. The data set you would need for this assignment can be found here: http://www-personal.umich.edu/ mejn/netdata/astro-ph.zip . This data set is a collection of scientific collaborations across researchers from the Astrophysics domain. Each node is a researcher, and each edge represents co-authorship of the two researchers together on a paper. The weight of each edge signifies indirectly, the strength and extent of collaboration between two such authors. For the assignment below, you are expected to first implement a framework that represents this co-authorship network in the form of an undirected weighted graph. We encourage you to use any graph analysis tools or packages you might want to or feel comfortable in using (SNAP for C++, NetworkX for Python, JUNG for Java etc). You can also find some here : http://www.stanford.edu/class/cs224w/resources.html Submission Instructions We expect you to be able to access your Dropbox folder on: http://coursework.stanford.edu (within your own space). Whichever files you want us to see are to be archived (or zipped) together into a single file and placed into this Dropbox folder. This file should be named of the format: < SUNetId > < Last-Name > < First-Name > HW1 : where these are your last and first names respectively. Within this file, we require the following at least : a. Your solution report. You can submit it as a .pdf or .doc. This report should be named as : < SUNetId > < Last-Name > < First-Name > HW1 Ans (.doc or .pdf) b. Any source code that you use towards obtaining your results stated in your solution report. Also include the mention of any tools whichever you use towards your solution(s). Questions 1. Network Characteristics (30 points - Sudarshan) Here, we would be dealing with not just the original network (henceforth called real world network), but also a configuration model (rewired network) and a G(n,m) Erdos-Renyi random network. Rewired network - For each node n i in the random network, create d i spokes (half-edges), where d i is the degree of the node i in the original network. Now randomly connect endpoints of these spokes - one possible way to do this is to create a random ordering of the spokes, and then simply connect those spokes that are adjacent in the ordering - connect spokes at positions 2 i + 1 and 2 i , for i = 1 ... . Notice that this procedure will likely create a multi-graph a graph with multiple edges (pairs of connected spokes) between a pair of nodes, and self-loops on nodes. Now, simplify the resulting multi-graph by collapsing multiple edges between
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hw1 - CS224W - Social and Information Network Analysis Fall...

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