Standard Network Analysis: location---organization

Standard Network Analysis: location---organization

Input data: location---organization

Start time: Tue Oct 18 12:08:42 2011

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Network Level Measures

MeasureValue
Row count66.000
Column count38.000
Link count24.000
Density0.010

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0350.0040.007
In-degree centrality [Unscaled]0.0007.0000.7891.472
Out-degree centrality0.0000.0960.0040.013
Out-degree centrality [Unscaled]0.00011.0000.4551.519

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): location---organization

RankOrganizationValueUnscaled
1hezbollah0.0357.000
2hamas0.0204.000
3united_nations0.0153.000
4militari0.0153.000
5armi0.0153.000
6palestinian_authority0.0102.000
7al-qaeda0.0102.000
8committe0.0051.000
9popular_front_for_the_liberation_of_palestine0.0051.000
10artilleri0.0051.000

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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): location---organization

RankLocationValueUnscaled
1israel0.09611.000
2lebanon0.0354.000
3syria0.0354.000
4gaza_strip0.0182.000
5al-rafah0.0091.000
6golan_heights0.0091.000
7chechnya0.0091.000
8germani0.0091.000
9saudi_arabia0.0091.000
10middle_east0.0091.000

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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----hezbollah-israel-
2----hamas-lebanon-
3----united_nations-syria-
4----militari-gaza_strip-
5----armi-al-rafah-
6----palestinian_authority-golan_heights-
7----al-qaeda-chechnya-
8----committe-germani-
9----popular_front_for_the_liberation_of_palestine-saudi_arabia-
10----artilleri-middle_east-