Standard Network Analysis: organization---agent

Standard Network Analysis: organization---agent

Input data: organization---agent

Start time: Tue Oct 18 12:09:00 2011

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Network Level Measures

MeasureValue
Row count38.000
Column count47.000
Link count20.000
Density0.011

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0530.0110.015
In-degree centrality [Unscaled]0.0002.0000.4260.574
Out-degree centrality0.0000.0850.0110.021
Out-degree centrality [Unscaled]0.0004.0000.5260.966

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---agent

RankAgentValueUnscaled
1yasser_arafat0.0532.000
2muhammad_horani0.0532.000
3abu_hafs0.0261.000
4muhammad_dahlan0.0261.000
5sirhan_sirhan0.0261.000
6jacob_dallal0.0261.000
7hassan_moayad0.0261.000
8raanan_gissin0.0261.000
9zelimkhan_yandarbiev0.0261.000
10georg_bush0.0261.000

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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---agent

RankOrganizationValueUnscaled
1hamas0.0854.000
2united_nations0.0643.000
3palestinian_authority0.0432.000
4al-qaeda0.0432.000
5hezbollah0.0432.000
6al-fatah0.0432.000
7fbi0.0211.000
8committe0.0211.000
9al-masri_brigad0.0211.000
10al-aksa0.0211.000

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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----yasser_arafat-hamas-
2----muhammad_horani-united_nations-
3----abu_hafs-palestinian_authority-
4----muhammad_dahlan-al-qaeda-
5----sirhan_sirhan-hezbollah-
6----jacob_dallal-al-fatah-
7----hassan_moayad-fbi-
8----raanan_gissin-committe-
9----zelimkhan_yandarbiev-al-masri_brigad-
10----georg_bush-al-aksa-