Standard Network Analysis: agent---organization

Standard Network Analysis: agent---organization

Input data: agent---organization

Start time: Tue Oct 18 12:07:32 2011

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Network Level Measures

MeasureValue
Row count47.000
Column count38.000
Link count25.000
Density0.014

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0500.0060.011
In-degree centrality [Unscaled]0.0007.0000.8681.507
Out-degree centrality0.0000.0350.0060.010
Out-degree centrality [Unscaled]0.0004.0000.7021.128

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): agent---organization

RankOrganizationValueUnscaled
1hamas0.0507.000
2administr0.0355.000
3al-qaeda0.0284.000
4islamic_jihad0.0213.000
5militari0.0142.000
6fbi0.0071.000
7treasury0.0071.000
8committe0.0071.000
9united_nations0.0071.000
10al-masri_brigad0.0071.000

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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): agent---organization

RankAgentValueUnscaled
1mokled_humaid0.0354.000
2yasser_arafat0.0354.000
3saddam_hussein0.0354.000
4georg_bush0.0263.000
5juan_zarat0.0182.000
6muhammad_dahlan0.0182.000
7colin_powel0.0182.000
8aziz_al-rantisi0.0182.000
9matthew_levitt0.0091.000
10abu_hafs0.0091.000

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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----hamas-mokled_humaid-
2----administr-yasser_arafat-
3----al-qaeda-saddam_hussein-
4----islamic_jihad-georg_bush-
5----militari-juan_zarat-
6----fbi-muhammad_dahlan-
7----treasury-colin_powel-
8----committe-aziz_al-rantisi-
9----united_nations-matthew_levitt-
10----al-masri_brigad-abu_hafs-