Standard Network Analysis: task-event---agent

Standard Network Analysis: task-event---agent

Input data: task-event---agent

Start time: Tue Oct 18 12:10:11 2011

Return to table of contents

Network Level Measures

MeasureValue
Row count22.000
Column count47.000
Link count8.000
Density0.008

Node Level Measures

MeasureMinMaxAvgStddev
In-degree centrality0.0000.0450.0080.017
In-degree centrality [Unscaled]0.0001.0000.1700.376
Out-degree centrality0.0000.0640.0080.016
Out-degree centrality [Unscaled]0.0003.0000.3640.771

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): task-event---agent

RankAgentValueUnscaled
1muhammad_sidr0.0451.000
2mokled_humaid0.0451.000
3yasser_arafat0.0451.000
4ismail_abu_shanab0.0451.000
5zelimkhan_yandarbiev0.0451.000
6georg_bush0.0451.000
7haviv_dodon0.0451.000
8saddam_hussein0.0451.000

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): task-event---agent

RankTaskValueUnscaled
1kill0.0643.000
2war0.0432.000
3support0.0211.000
4suspect0.0211.000
5arrest0.0211.000

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----muhammad_sidr-kill-
2----mokled_humaid-war-
3----yasser_arafat-support-
4----ismail_abu_shanab-suspect-
5----zelimkhan_yandarbiev-arrest-
6----georg_bush-crime-
7----haviv_dodon-intifada-
8----saddam_hussein-takeov-
9----marwan_barghouti-airstrike-
10----bernard_sabella-raid-