Standard Network Analysis: Agent x Resource

Standard Network Analysis: Agent x Resource

Input data: Agent x Resource

Start time: Tue Oct 18 11:45:57 2011

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Network Level Measures

MeasureValue
Row count16.000
Column count4.000
Link count13.000
Density0.203

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.1250.3130.2030.081
In-degree centrality [Unscaled]2.0005.0003.2501.299
Out-degree centrality0.0000.7500.2030.220
Out-degree centrality [Unscaled]0.0003.0000.8130.882

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
1building for bombmaking0.3135.000
2bomb material0.2504.000
3money0.1252.000
4truck0.1252.000

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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
1Abdullah Ahmed Abdullah0.7503.000
2Fazul Abdullah Mohammed0.5002.000
3Ahmed Khalfan Ghailani0.5002.000
4Khalfan Khamis Mohamed0.2501.000
5Mohammed Sadiq Odeh0.2501.000
6Wadih al Hage0.2501.000
7Usama Bin Ladin0.2501.000
8Mohammed Salim0.2501.000
9Abdal Rahmad0.2501.000

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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----building for bombmaking-Abdullah Ahmed Abdullah-
2----bomb material-Fazul Abdullah Mohammed-
3----money-Ahmed Khalfan Ghailani-
4----truck-Khalfan Khamis Mohamed-
5------Mohammed Sadiq Odeh-
6------Wadih al Hage-
7------Usama Bin Ladin-
8------Mohammed Salim-
9------Abdal Rahmad-
10------Mohammed Rashed Daoud al-Owhali-