Standard Network Analysis: agent x resource

Standard Network Analysis: agent x resource

Input data: agent x resource

Start time: Tue Oct 18 11:57:47 2011

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Network Level Measures

MeasureValue
Row count18.000
Column count13.000
Link count18.000
Density0.077

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0560.1670.0770.035
In-degree centrality [Unscaled]1.0003.0001.3850.625
Out-degree centrality0.0000.2310.0770.063
Out-degree centrality [Unscaled]0.0003.0001.0000.816

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 resource

RankResourceValueUnscaled
1bomb_material0.1673.000
2surveillance_equipment0.1112.000
3oxygen0.1112.000
4acetylene0.1112.000
5false_travel_documents0.0561.000
6bomb_and_detonation_device0.0561.000
7stun_grenades0.0561.000
8toyota_dyna_truck0.0561.000
9money0.0561.000
10vehicle0.0561.000

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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 resource

RankAgentValueUnscaled
1Fazul Abdullah Mohammed0.2313.000
2Khalfan Khamis Mohamed0.1542.000
3Ahmed Khalfan Ghalilani0.1542.000
4Wadih el-Hage0.1542.000
5Muhammed Atef0.0771.000
6Abdullah Ahmed Abdullah0.0771.000
7Fahid Mohammed Ally Msalam0.0771.000
8Osama Bin Laden0.0771.000
9Al Owali0.0771.000
10Ali Mohammed0.0771.000

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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----bomb_material-Fazul Abdullah Mohammed-
2----surveillance_equipment-Khalfan Khamis Mohamed-
3----oxygen-Ahmed Khalfan Ghalilani-
4----acetylene-Wadih el-Hage-
5----false_travel_documents-Muhammed Atef-
6----bomb_and_detonation_device-Abdullah Ahmed Abdullah-
7----stun_grenades-Fahid Mohammed Ally Msalam-
8----toyota_dyna_truck-Osama Bin Laden-
9----money-Al Owali-
10----vehicle-Ali Mohammed-