Standard Network Analysis: organization---location

Standard Network Analysis: organization---location

Input data: organization---location

Start time: Tue Oct 18 12:09:12 2011

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Network Level Measures

MeasureValue
Row count38.000
Column count66.000
Link count35.000
Density0.014

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0790.0070.015
In-degree centrality [Unscaled]0.0006.0000.5611.130
Out-degree centrality0.0000.0380.0070.010
Out-degree centrality [Unscaled]0.0005.0000.9741.267

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): organization---location

RankLocationValueUnscaled
1israel0.0796.000
2syria0.0665.000
3west_bank0.0393.000
4gaza_strip0.0262.000
5iraq0.0262.000
6lebanon0.0262.000
7afghanistan0.0262.000
8ramallah0.0262.000
9aachen0.0262.000
10training_camp0.0131.000

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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): organization---location

RankOrganizationValueUnscaled
1hezbollah0.0385.000
2headquart0.0304.000
3united_nations0.0233.000
4hamas0.0233.000
5militari0.0233.000
6islamic_jihad0.0152.000
7administr0.0152.000
8al-aksa0.0152.000
9al-qaeda0.0152.000
10troop0.0152.000

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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----israel-hezbollah-
2----syria-headquart-
3----west_bank-united_nations-
4----gaza_strip-hamas-
5----iraq-militari-
6----lebanon-islamic_jihad-
7----afghanistan-administr-
8----ramallah-al-aksa-
9----aachen-al-qaeda-
10----training_camp-troop-