# Machine Learning/Kaggle Social Network Contest/Network Description

From Noisebridge

< Machine Learning | Kaggle Social Network Contest(Difference between revisions)

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* It contains 27 subgraphs This means that it can be broken down into at least two discrete subgraphs. | * It contains 27 subgraphs This means that it can be broken down into at least two discrete subgraphs. | ||

** c.f. [http://cneurocvs.rmki.kfki.hu/igraph/doc/R/clusters.html igraph clustering] | ** c.f. [http://cneurocvs.rmki.kfki.hu/igraph/doc/R/clusters.html igraph clustering] | ||

− | ** There is one very large cluster containing all but 154 verticies, then 4 with size 10 - 37, 8 sized 3 - 7 | + | ** There is one very large cluster containing all but 154 verticies, then 4 with size 10 - 37, 8 sized 3 - 7 and 13 size 2 |

+ | ** note that igraph seems to create a vertex labelled 0 but the labels in the traindata file range from 1 to 1133547 | ||

* I also grabbed the number of strongly connected subgraphs | * I also grabbed the number of strongly connected subgraphs |

## Revision as of 13:19, 23 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

## Conectivity

"A digraph is strongly connected if every vertex is reachable from every other following the directions of the arcs. On the contrary, a digraph is weakly connected if its underlying undirected graph is connected. A weakly connected graph can be thought of as a digraph in which every vertex is "reachable" from every other but not necessarily following the directions of the arcs. A strong orientation is an orientation that produces a strongly connected digraph." wikipedia

- The Graph is
**not**weakly connected - It contains 27 subgraphs This means that it can be broken down into at least two discrete subgraphs.
- c.f. igraph clustering
- There is one very large cluster containing all but 154 verticies, then 4 with size 10 - 37, 8 sized 3 - 7 and 13 size 2
- note that igraph seems to create a vertex labelled 0 but the labels in the traindata file range from 1 to 1133547

- I also grabbed the number of strongly connected subgraphs

Cluster Size | 1 | 2 | 3 | 4 | 5 | 9 | 10 | 32464 |
---|---|---|---|---|---|---|---|---|

freq | 1100647 | 162 | 18 | 5 | 4 | 1 | 1 | 1 |

- Diameter of the directed graph is 14
- 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"