Input data: organization---organization
Start time: Tue Oct 18 12:09:18 2011
Network Level Measures
Measure Value Row count 38.000 Column count 38.000 Link count 28.000 Density 0.019 Components of 1 node (isolates) 17 Components of 2 nodes (dyadic isolates) 1 Components of 3 or more nodes 2 Reciprocity 0.087 Characteristic path length 2.653 Clustering coefficient 0.136 Network levels (diameter) 8.000 Network fragmentation 0.855 Krackhardt connectedness 0.145 Krackhardt efficiency 0.905 Krackhardt hierarchy 0.957 Krackhardt upperboundedness 0.500 Degree centralization 0.039 Betweenness centralization 0.007 Closeness centralization 0.001 Eigenvector centralization 1.091 Reciprocal (symmetric)? No (8% of the links are reciprocal) Node Level Measures
Measure Min Max Avg Stddev Total degree centrality 0.000 0.042 0.005 0.008 Total degree centrality [Unscaled] 0.000 22.000 2.395 4.252 In-degree centrality 0.000 0.045 0.005 0.009 In-degree centrality [Unscaled] 0.000 12.000 1.316 2.341 Out-degree centrality 0.000 0.064 0.005 0.012 Out-degree centrality [Unscaled] 0.000 17.000 1.316 3.188 Eigenvector centrality 0.000 1.113 0.079 0.215 Eigenvector centrality [Unscaled] 0.000 0.787 0.056 0.152 Eigenvector centrality per component 0.000 0.290 0.029 0.057 Closeness centrality 0.004 0.005 0.004 0.000 Closeness centrality [Unscaled] 0.000 0.000 0.000 0.000 In-Closeness centrality 0.004 0.004 0.004 0.000 In-Closeness centrality [Unscaled] 0.000 0.000 0.000 0.000 Betweenness centrality 0.000 0.008 0.001 0.002 Betweenness centrality [Unscaled] 0.000 10.000 0.921 2.310 Hub centrality 0.000 1.289 0.058 0.222 Authority centrality 0.000 1.133 0.074 0.217 Information centrality 0.000 0.172 0.026 0.045 Information centrality [Unscaled] 0.000 3.951 0.605 1.033 Clique membership count 0.000 4.000 0.395 0.875 Simmelian ties 0.000 0.000 0.000 0.000 Simmelian ties [Unscaled] 0.000 0.000 0.000 0.000 Clustering coefficient 0.000 1.000 0.136 0.253 Key Nodes
This chart shows the Organization that is repeatedly top-ranked in the measures listed below. The value shown is the percentage of measures for which the Organization was ranked in the top three.
Total degree centrality
The Total Degree Centrality of a node is the normalized sum of its row and column degrees. Individuals or organizations who are "in the know" are those who are linked to many others and so, by virtue of their position have access to the ideas, thoughts, beliefs of many others. Individuals who are "in the know" are identified by degree centrality in the relevant social network. Those who are ranked high on this metrics have more connections to others in the same network. The scientific name of this measure is total degree centrality and it is calculated on the agent by agent matrices.
Input network: organization---organization (size: 38, density: 0.0193906)
Rank Organization Value Unscaled Context* 1 hamas 0.042 22.000 1.006 2 islamic_jihad 0.025 13.000 0.240 3 al-qaeda 0.013 7.000 -0.271 4 hezbollah 0.013 7.000 -0.271 5 militari 0.013 7.000 -0.271 6 network 0.010 5.000 -0.441 7 al-aksa 0.010 5.000 -0.441 8 palestinian_authority 0.008 4.000 -0.526 9 artilleri 0.006 3.000 -0.611 10 guerrilla 0.004 2.000 -0.697 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.005 Mean in random network: 0.019 Std.dev: 0.008 Std.dev in random network: 0.022 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---organization
Rank Organization Value Unscaled 1 hamas 0.045 12.000 2 militari 0.026 7.000 3 islamic_jihad 0.019 5.000 4 al-aksa 0.015 4.000 5 network 0.011 3.000 6 artilleri 0.011 3.000 7 militia 0.008 2.000 8 headquart 0.008 2.000 9 al-qaeda 0.008 2.000 10 fbi 0.004 1.000 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---organization
Rank Organization Value Unscaled 1 hamas 0.064 17.000 2 islamic_jihad 0.030 8.000 3 al-qaeda 0.023 6.000 4 hezbollah 0.023 6.000 5 palestinian_authority 0.015 4.000 6 network 0.008 2.000 7 guerrilla 0.004 1.000 8 united_nations 0.004 1.000 9 treasuridepart 0.004 1.000 10 deleg 0.004 1.000 Eigenvector centrality
Calculates the principal eigenvector of the network. A node is central to the extent that its neighbors are central. Leaders of strong cliques are individuals who or organizations who are collected to others that are themselves highly connected to each other. In other words, if you have a clique then the individual most connected to others in the clique and other cliques, is the leader of the clique. Individuals or organizations who are connected to many otherwise isolated individuals or organizations will have a much lower score in this measure then those that are connected to groups that have many connections themselves. The scientific name of this measure is eigenvector centrality and it is calculated on agent by agent matrices.
Input network: organization---organization (size: 38, density: 0.0193906)
Rank Organization Value Unscaled Context* 1 hamas 1.113 0.787 -0.007 2 islamic_jihad 0.653 0.462 -1.205 3 militari 0.375 0.265 -1.931 4 palestinian_authority 0.309 0.219 -2.101 5 al-aksa 0.264 0.187 -2.219 6 treasuridepart 0.117 0.083 -2.602 7 headquart 0.117 0.083 -2.602 8 al-qaeda 0.038 0.027 -2.807 9 network 0.010 0.007 -2.881 10 united_nations 0.003 0.002 -2.898 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.079 Mean in random network: 1.116 Std.dev: 0.215 Std.dev in random network: 0.384 Eigenvector centrality per component
Calculates the principal eigenvector of the network. A node is central to the extent that its neighbors are central. Each component is extracted as a separate network, Eigenvector Centrality is computed on it and scaled according to the component size. The scores are then combined into a single result vector.
Input network(s): organization---organization
Rank Organization Value 1 hamas 0.290 2 islamic_jihad 0.170 3 militari 0.098 4 hezbollah 0.091 5 palestinian_authority 0.081 6 artilleri 0.076 7 al-aksa 0.069 8 committe 0.037 9 plo 0.037 10 militia 0.035 Closeness centrality
The average closeness of a node to the other nodes in a network (also called out-closeness). Loosely, Closeness is the inverse of the average distance in the network from the node to all other nodes.
Input network: organization---organization (size: 38, density: 0.0193906)
Rank Organization Value Unscaled Context* 1 deleg 0.005 0.000 917.086 2 united_nations 0.004 0.000 916.722 3 palestinian_authority 0.004 0.000 916.709 4 hamas 0.004 0.000 916.382 5 islamic_jihad 0.004 0.000 916.380 6 al-qaeda 0.004 0.000 916.378 7 hezbollah 0.004 0.000 916.056 8 guerrilla 0.004 0.000 916.052 9 network 0.004 0.000 915.454 10 treasuridepart 0.004 0.000 915.453 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.004 Mean in random network: -0.360 Std.dev: 0.000 Std.dev in random network: 0.000 In-Closeness centrality
The average closeness of a node from the other nodes in a network. Loosely, Closeness is the inverse of the average distance in the network to the node and from all other nodes.
Input network(s): organization---organization
Rank Organization Value Unscaled 1 militari 0.004 0.000 2 headquart 0.004 0.000 3 al-aksa 0.004 0.000 4 fbi 0.004 0.000 5 hawala 0.004 0.000 6 militia 0.004 0.000 7 administr 0.004 0.000 8 treasuridepart 0.004 0.000 9 network 0.004 0.000 10 al-qaeda 0.004 0.000 Betweenness centrality
The Betweenness Centrality of node v in a network is defined as: across all node pairs that have a shortest path containing v, the percentage that pass through v. Individuals or organizations that are potentially influential are positioned to broker connections between groups and to bring to bear the influence of one group on another or serve as a gatekeeper between groups. This agent occurs on many of the shortest paths between other agents. The scientific name of this measure is betweenness centrality and it is calculated on agent by agent matrices.
Input network: organization---organization (size: 38, density: 0.0193906)
Rank Organization Value Unscaled Context* 1 al-qaeda 0.008 10.000 -0.764 2 hamas 0.005 7.000 -0.787 3 network 0.005 6.000 -0.795 4 united_nations 0.005 6.000 -0.795 5 hezbollah 0.002 3.000 -0.818 6 al-aksa 0.002 2.000 -0.826 7 treasuridepart 0.001 1.000 -0.833 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.001 Mean in random network: 0.082 Std.dev: 0.002 Std.dev in random network: 0.098 Hub centrality
A node is hub-central to the extent that its out-links are to nodes that have many in-links. Individuals or organizations that act as hubs are sending information to a wide range of others each of whom has many others reporting to them. Technically, an agent is hub-central if its out-links are to agents that have many other agents sending links to them. The scientific name of this measure is hub centrality and it is calculated on agent by agent matrices.
Input network(s): organization---organization
Rank Organization Value 1 hamas 1.289 2 islamic_jihad 0.458 3 palestinian_authority 0.354 4 al-qaeda 0.043 5 treasuridepart 0.033 6 al-aksa 0.014 7 united_nations 0.000 8 hezbollah 0.000 9 shia 0.000 10 network 0.000 Authority centrality
A node is authority-central to the extent that its in-links are from nodes that have many out-links. Individuals or organizations that act as authorities are receiving information from a wide range of others each of whom sends information to a large number of others. Technically, an agent is authority-central if its in-links are from agents that have are sending links to many others. The scientific name of this measure is authority centrality and it is calculated on agent by agent matrices.
Input network(s): organization---organization
Rank Organization Value 1 hamas 1.133 2 islamic_jihad 0.664 3 militari 0.373 4 al-aksa 0.316 5 headquart 0.134 6 treasuridepart 0.133 7 palestinian_authority 0.036 8 network 0.013 9 al-qaeda 0.005 10 administr 0.004 Information centrality
Calculate the Stephenson and Zelen information centrality measure for each node.
Input network(s): organization---organization
Rank Organization Value Unscaled 1 hamas 0.172 3.951 2 islamic_jihad 0.135 3.096 3 al-qaeda 0.126 2.897 4 hezbollah 0.116 2.658 5 palestinian_authority 0.100 2.307 6 network 0.067 1.540 7 united_nations 0.044 1.006 8 al-aksa 0.043 0.989 9 deleg 0.042 0.977 10 treasuridepart 0.042 0.966 Clique membership count
The number of distinct cliques to which each node belongs. Individuals or organizations who are high in number of cliques are those that belong to a large number of distinct cliques. A clique is defined as a group of three or more actors that have many connections to each other and relatively fewer connections to those in other groups. The scientific name of this measure is clique count and it is calculated on the agent by agent matrices.
Input network(s): organization---organization
Rank Organization Value 1 hamas 4.000 2 al-aksa 3.000 3 islamic_jihad 2.000 4 militia 1.000 5 treasuridepart 1.000 6 headquart 1.000 7 hezbollah 1.000 8 militari 1.000 9 shia 1.000 Simmelian ties
The normalized number of Simmelian ties of each node.
Input network(s): organization---organization
Rank Organization Value Unscaled 1 All nodes have this value 0.000 Clustering coefficient
Measures the degree of clustering in a network by averaging the clustering coefficient of each node, which is defined as the density of the node's ego network.
Input network(s): organization---organization
Rank Organization Value 1 palestinian_authority 1.000 2 administr 1.000 3 treasuridepart 0.500 4 headquart 0.500 5 militari 0.444 6 islamic_jihad 0.333 7 al-aksa 0.313 8 militia 0.250 9 united_nations 0.250 10 shia 0.250 Key Nodes Table
This shows the top scoring nodes side-by-side for selected measures.
Rank Betweenness centrality Closeness centrality Eigenvector centrality Eigenvector centrality per component In-degree centrality In-Closeness centrality Out-degree centrality Total degree centrality 1 al-qaeda deleg hamas hamas hamas militari hamas hamas 2 hamas united_nations islamic_jihad islamic_jihad militari headquart islamic_jihad islamic_jihad 3 network palestinian_authority militari militari islamic_jihad al-aksa al-qaeda al-qaeda 4 united_nations hamas palestinian_authority hezbollah al-aksa fbi hezbollah hezbollah 5 hezbollah islamic_jihad al-aksa palestinian_authority network hawala palestinian_authority militari 6 al-aksa al-qaeda treasuridepart artilleri artilleri militia network network 7 treasuridepart hezbollah headquart al-aksa militia administr guerrilla al-aksa 8 fbi guerrilla al-qaeda committe headquart treasuridepart united_nations palestinian_authority 9 agenc network network plo al-qaeda network treasuridepart artilleri 10 polic treasuridepart united_nations militia fbi al-qaeda deleg guerrilla