Standard Network Analysis: organization---knowledge

Standard Network Analysis: organization---knowledge

Input data: organization---knowledge

Start time: Tue Oct 18 12:09:06 2011

Return to table of contents

Network Level Measures

MeasureValue
Row count38.000
Column count32.000
Link count14.000
Density0.012

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0530.0040.010
In-degree centrality [Unscaled]0.0006.0000.5001.118
Out-degree centrality0.0000.0420.0040.011
Out-degree centrality [Unscaled]0.0004.0000.4211.016

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---knowledge

RankKnowledgeValueUnscaled
1report0.0536.000
2call0.0182.000
3manual0.0091.000
4messag0.0091.000
5footag0.0091.000
6al-jazeera0.0091.000
7fbi0.0091.000
8video0.0091.000
9analyst0.0091.000
10inform0.0091.000

Back to top

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---knowledge

RankOrganizationValueUnscaled
1network0.0424.000
2al-qaeda0.0424.000
3militari0.0313.000
4fbi0.0101.000
5united_nations0.0101.000
6hezbollah0.0101.000
7al-fatah0.0101.000
8armi0.0101.000

Back to top

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----report-network-
2----call-al-qaeda-
3----manual-militari-
4----messag-fbi-
5----footag-united_nations-
6----al-jazeera-hezbollah-
7----fbi-al-fatah-
8----video-armi-
9----analyst-agenc-
10----inform-polic-