Machine Learning/Kaggle Social Network Contest/Network Description: Difference between revisions
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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 | ||
* 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"