What if you need a sub-network from a larger one, and how would you extract it? I’ll walk you through the steps of how to do a Snowball extraction, (or extraction by steps). I have no doubt this goes by many names, but Snowball is the name I’ve been familiar with for years.
Assume you are given a network, and by network I mean a graph structure with data attributes on the nodes and/or edges such that the graph represents data connected with respect to a particular context. For example, take a simple graph:
Add some names and now it is a simple social network:
Graph + Data = Network
A Snowball Extration
Lets start with the following example network and perform a snowball extraction 3 steps/hops out.
Step 1: given a set of seed nodes: (2, 16), find all nodes 1 step or hop out from the seed nodes. The nodes we are interested in are the neighbors of the seed nodes along outgoing edges, (in this example we will be considering the directionality of the edges). Seed nodes are in green:
Step 2: Now gather the new nodes found in Step 1: (1, 3, 9, 10, 36) and repeat the process:
Step 3: Get the new nodes from step 2: (4, 6, 8, 1, 12, 17, 34) and repeat:
Step 4: With the new nodes from step 3: (5, 7, 13, 15, 18, 19, 33), combine all found nodes and edges for the resulting sub-network:
Note that using different seed nodes you may end up with a drastically different subnetwork and much depends on the structure and properties of the main network. Additionally, how you handle duplicate edges, self-loops, and parallel-edges are completely determined by your problem at hand. I’ve attempted to formalize the steps as pseudo-code below, but again the complexities of the problem at hand will affect how this should be implemented.
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