Standard Network Analysis: task x event

Standard Network Analysis: task x event

Input data: task x event

Start time: Thu Nov 17 13:55:19 2011

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Network Level Measures

MeasureValue
Row count18.000
Column count14.000
Link count15.000
Density0.060

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.2220.0600.077
In-degree centrality [Unscaled]0.0004.0001.0711.387
Out-degree centrality0.0000.1430.0600.036
Out-degree centrality [Unscaled]0.0002.0000.8330.500

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): task x event

RankEventValueUnscaled
1summit_meeting0.2224.000
2sgc_meeting0.2224.000
3replace_jarren0.1112.000
4escape_tunnels0.1112.000
5revanna_meeting0.0561.000
6revanna_bombardment0.0561.000
7gate_attack0.0561.000

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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): task x event

RankTaskValueUnscaled
1inflitrate_yuWorld0.1432.000
2poison_summit0.0711.000
3infiltrate_summit0.0711.000
4fly_ship_to_yuWorld0.0711.000
5poison_jaffa_at_gate0.0711.000
6create_poison0.0711.000
7replace_jerran0.0711.000
8create_memory_drug0.0711.000
9present_plan_to_sgc0.0711.000
10spy_on_summit0.0711.000

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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----summit_meeting-inflitrate_yuWorld-
2----sgc_meeting-poison_summit-
3----replace_jarren-infiltrate_summit-
4----escape_tunnels-fly_ship_to_yuWorld-
5----revanna_meeting-poison_jaffa_at_gate-
6----revanna_bombardment-create_poison-
7----gate_attack-replace_jerran-
8----tollana_attack-create_memory_drug-
9----bring_crystals_to_sgc-present_plan_to_sgc-
10----osiris_arrives-spy_on_summit-