Standard Network Analysis: agent x organization

Standard Network Analysis: agent x organization

Input data: agent x organization

Start time: Tue Oct 18 11:49:01 2011

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Network Level Measures

MeasureValue
Row count27.000
Column count2.000
Link count21.000
Density0.389

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.4810.2410.241
In-degree centrality [Unscaled]0.00026.00013.00013.000
Out-degree centrality0.0000.5000.2410.159
Out-degree centrality [Unscaled]0.0002.0000.9630.637

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 x organization

RankOrganizationValueUnscaled
1al_qaeda0.48126.000

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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 x organization

RankAgentValueUnscaled
1khalfan_mohamed0.5002.000
2ahmed_ghailani0.5002.000
3swedan_sheikh0.5002.000
4mustafa_fadhil0.5002.000
5fahid_msalam0.5002.000
6mohamed_owhali0.2501.000
7mohammed_odeh0.2501.000
8fazul_mohammed0.2501.000
9wadih_el-hage0.2501.000
10bin_laden0.2501.000

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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----al_qaeda-khalfan_mohamed-
2----united_states_of_america-ahmed_ghailani-
3------swedan_sheikh-
4------mustafa_fadhil-
5------fahid_msalam-
6------mohamed_owhali-
7------mohammed_odeh-
8------fazul_mohammed-
9------wadih_el-hage-
10------bin_laden-