Standard Network Analysis: task-event---resource

Standard Network Analysis: task-event---resource

Input data: task-event---resource

Start time: Tue Oct 18 12:10:36 2011

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Network Level Measures

MeasureValue
Row count22.000
Column count59.000
Link count7.000
Density0.005

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0610.0030.009
In-degree centrality [Unscaled]0.0004.0000.1690.615
Out-degree centrality0.0000.0230.0030.006
Out-degree centrality [Unscaled]0.0004.0000.4550.988

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-event---resource

RankResourceValueUnscaled
1soldier0.0614.000
2weapon0.0302.000
3polic0.0151.000
4ah-64_apache0.0151.000
5sponsor0.0151.000
6arm0.0151.000

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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-event---resource

RankTaskValueUnscaled
1kill0.0234.000
2support0.0112.000
3confisc0.0112.000
4arrest0.0061.000
5accus0.0061.000

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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----soldier-kill-
2----weapon-support-
3----polic-confisc-
4----ah-64_apache-arrest-
5----sponsor-accus-
6----arm-crime-
7----financi-intifada-
8----missil-takeov-
9----hospit-airstrike-
10----training_camp-raid-