Standard Network Analysis: resource x task

Standard Network Analysis: resource x task

Input data: resource x task

Start time: Thu Nov 17 13:55:14 2011

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Network Level Measures

MeasureValue
Row count7.000
Column count18.000
Link count8.000
Density0.063

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.2860.0630.085
In-degree centrality [Unscaled]0.0002.0000.4440.598
Out-degree centrality0.0000.1110.0630.035
Out-degree centrality [Unscaled]0.0002.0001.1430.639

Key Nodes

In-degree centrality

The In Degree Centrality of a node is its normalized in-degree. For any node, e.g. an individual or a resource, the in-links are the connections that the node of interest receives from other nodes. For example, imagine an agent by knowledge matrix then the number of in-links a piece of knowledge has is the number of agents that are connected to. The scientific name of this measure is in-degree and it is calculated on the agent by agent matrices.

Input network(s): resource x task

RankTaskValueUnscaled
1infiltrate_summit0.2862.000
2poison_summit0.1431.000
3poison_jaffa_at_gate0.1431.000
4replace_jerran0.1431.000
5create_memory_drug0.1431.000
6find_tunnel_crystals0.1431.000
7hide_data_crystal0.1431.000

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Out-degree centrality

For any node, e.g. an individual or a resource, the out-links are the connections that the node of interest sends to other nodes. For example, imagine an agent by knowledge matrix then the number of out-links an agent would have is the number of pieces of knowledge it is connected to. The scientific name of this measure is out-degree and it is calculated on the agent by agent matrices. Individuals or organizations who are high in most knowledge have more expertise or are associated with more types of knowledge than are others. If no sub-network connecting agents to knowledge exists, then this measure will not be calculated. The scientific name of this measure is out degree centrality and it is calculated on agent by knowledge matrices. Individuals or organizations who are high in "most resources" have more resources or are associated with more types of resources than are others. If no sub-network connecting agents to resources exists, then this measure will not be calculated. The scientific name of this measure is out degree centrality and it is calculated on agent by resource matrices.

Input network(s): resource x task

RankResourceValueUnscaled
1symbiote_poison0.1112.000
2memory_altering_drug0.1112.000
3cargo_ship0.0561.000
4tok'ra_tunneling_crystals0.0561.000
5data_crystal0.0561.000
6reole_chameleon0.0561.000

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Key Nodes Table

This shows the top scoring nodes side-by-side for selected measures.

RankBetweenness centralityCloseness centralityEigenvector centralityEigenvector centrality per componentIn-degree centralityIn-Closeness centralityOut-degree centralityTotal degree centrality
1----infiltrate_summit-symbiote_poison-
2----poison_summit-memory_altering_drug-
3----poison_jaffa_at_gate-cargo_ship-
4----replace_jerran-tok'ra_tunneling_crystals-
5----create_memory_drug-data_crystal-
6----find_tunnel_crystals-reole_chameleon-
7----hide_data_crystal-tok'ra_communicator-
8----fly_ship_to_yuWorld---
9----create_poison---
10----present_plan_to_sgc---