Standard Network Analysis: agent---location

Standard Network Analysis: agent---location

Input data: agent---location

Start time: Tue Oct 18 12:07:26 2011

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Network Level Measures

MeasureValue
Row count47.000
Column count66.000
Link count12.000
Density0.004

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0640.0040.013
In-degree centrality [Unscaled]0.0003.0000.1820.601
Out-degree centrality0.0000.0300.0040.008
Out-degree centrality [Unscaled]0.0002.0000.2550.525

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---location

RankLocationValueUnscaled
1iraq0.0643.000
2israel0.0643.000
3egypt0.0432.000
4camp_david0.0211.000
5lebanon0.0211.000
6palestine0.0211.000
7ramallah0.0211.000

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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---location

RankAgentValueUnscaled
1yasser_arafat0.0302.000
2georg_bush0.0302.000
3bill_clinton0.0151.000
4omar_sulieman0.0151.000
5abdel_nasser0.0151.000
6shaul_mofaz0.0151.000
7ariel_sharon0.0151.000
8saddam_hussein0.0151.000
9kofi_annan0.0151.000
10colin_powel0.0151.000

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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----iraq-yasser_arafat-
2----israel-georg_bush-
3----egypt-bill_clinton-
4----camp_david-omar_sulieman-
5----lebanon-abdel_nasser-
6----palestine-shaul_mofaz-
7----ramallah-ariel_sharon-
8----gaza_strip-saddam_hussein-
9----training_camp-kofi_annan-
10----al-musayyi-colin_powel-