Machine Learning/Kaggle Social Network Contest/Network Description

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(Created page with 'Here we can put the descriptive statistics of the network: * Number of fully sampled nodes: 37,689 ** ie the unique "outnodes" in the edge list * Total number of nodes: 1,133,5…')
 
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* Total number of nodes: 1,133,547
 
* Total number of nodes: 1,133,547
 
* number of edges: 7,237,983
 
* number of edges: 7,237,983
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* The Graph is '''not''' weakly connected! This means that it can be broken down into at least two discrete subgraphs.
  
 
* Diameter of the directed graph
 
* Diameter of the directed graph

Revision as of 20:29, 22 November 2010

Here we can put the descriptive statistics of the network:

  • Number of fully sampled nodes: 37,689
    • ie the unique "outnodes" in the edge list
  • Total number of nodes: 1,133,547
  • number of edges: 7,237,983
  • The Graph is not weakly connected! This means that it can be broken down into at least two discrete subgraphs.
  • Diameter of the directed graph
    • This is the longest of the shortest directed paths between two nodes
    • R igraph
      • diameter (dg, directed = TRUE, unconnected = TRUE)
      • Was taking forever so I aborted (after 34 minutes...)
  • Total number of direct neighbours out: 7 275 672, in: 508 688, all: 7 473 273
    • For each of our 38k I calculated the number of outbound neighbours and summed it
    • R igraph:
      • sum(neighborhood.size(dg, 1, nodes=myGuys, mode="out"))
      • mode = "in", "out" or "all"
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