Calculates common social network measures on each selected input network.
Network resource x resource
Block Model - Newman's Clustering Algorithm
Network Level Measures
Measure Value Row count 1490.000 Column count 1490.000 Link count 19025.000 Density 0.009 Components of 1 node (isolates) 266 Components of 2 nodes (dyadic isolates) 1 Components of 3 or more nodes 1 Reciprocity 0.138 Characteristic path length 3.390 Clustering coefficient 0.146 Network levels (diameter) 9.000 Network fragmentation 0.327 Krackhardt connectedness 0.673 Krackhardt efficiency 0.979 Krackhardt hierarchy 0.529 Krackhardt upperboundedness 0.925 Degree centralization 0.148 Betweenness centralization 0.098 Closeness centralization 0.001 Eigenvector centralization 0.213 Reciprocal (symmetric)? No (13% of the links are reciprocal)
Node Level Measures
Measure Min Max Avg Stddev Total degree centrality 0.000 0.157 0.009 0.014 Total degree centrality [Unscaled] 0.000 467.000 25.535 42.771 In-degree centrality 0.000 0.226 0.009 0.020 In-degree centrality [Unscaled] 0.000 337.000 12.768 29.828 Out-degree centrality 0.000 0.172 0.009 0.014 Out-degree centrality [Unscaled] 0.000 256.000 12.768 20.724 Eigenvector centrality 0.000 0.232 0.020 0.031 Eigenvector centrality [Unscaled] 0.000 0.164 0.014 0.022 Eigenvector centrality per component 0.000 0.135 0.011 0.018 Closeness centrality 0.001 0.002 0.001 0.001 Closeness centrality [Unscaled] 0.000 0.000 0.000 0.000 In-Closeness centrality 0.001 0.002 0.002 0.001 In-Closeness centrality [Unscaled] 0.000 0.000 0.000 0.000 Betweenness centrality 0.000 0.099 0.001 0.004 Betweenness centrality [Unscaled] 0.000 218463.953 1574.069 7759.777 Hub centrality 0.000 0.200 0.020 0.031 Authority centrality 0.000 0.321 0.014 0.034 Information centrality 0.000 0.001 0.001 0.001 Information centrality [Unscaled] 0.000 3.892 1.808 1.407 Clique membership count 0.000 26845.000 326.603 1532.945 Simmelian ties 0.000 0.066 0.002 0.005 Simmelian ties [Unscaled] 0.000 99.000 2.368 6.831 Clustering coefficient 0.000 1.000 0.146 0.133
Key Nodes
This chart shows the Resource that is repeatedly top-ranked in the measures listed below. The value shown is the percentage of measures for which the Resource 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: resource x resource (size: 1490, density: 0.00856943)
Rank Resource Value Unscaled Context* 1 blogsforbush.com 0.157 467.000 62.061 2 dailykos.com 0.129 383.000 50.252 3 instapundit.com 0.122 362.000 47.300 4 atrios.blogspot.com 0.117 350.000 45.613 5 talkingpointsmemo.com 0.095 282.000 36.054 6 washingtonmonthly.com 0.086 256.000 32.399 7 drudgereport.com 0.082 243.000 30.572 8 powerlineblog.com 0.079 235.000 29.447 9 michellemalkin.com 0.077 228.000 28.463 10 hughhewitt.com 0.076 225.000 28.041 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.009 Mean in random network: 0.009 Std.dev: 0.014 Std.dev in random network: 0.002 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): resource x resource
Rank Resource Value Unscaled 1 dailykos.com 0.226 337.000 2 instapundit.com 0.185 276.000 3 talkingpointsmemo.com 0.180 268.000 4 atrios.blogspot.com 0.177 263.000 5 drudgereport.com 0.160 238.000 6 powerlineblog.com 0.148 220.000 7 blogsforbush.com 0.142 211.000 8 washingtonmonthly.com 0.135 201.000 9 michellemalkin.com 0.134 200.000 10 truthlaidbear.com 0.126 187.000 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): resource x resource
Rank Resource Value Unscaled 1 blogsforbush.com 0.172 256.000 2 newleftblogs.blogspot.com 0.094 140.000 3 madkane.com/notable.html 0.088 131.000 4 politicalstrategy.org 0.088 131.000 5 cayankee.blogs.com 0.083 123.000 6 liberaloasis.com 0.077 115.000 7 lashawnbarber.com 0.076 113.000 8 gevkaffeegal.typepad.com/the_alliance 0.074 110.000 9 presidentboxer.blogspot.com 0.073 109.000 10 corrente.blogspot.com 0.071 106.000 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: resource x resource (size: 1490, density: 0.00856943)
Rank Resource Value Unscaled Context* 1 dailykos.com 0.232 0.164 -3.370 2 atrios.blogspot.com 0.227 0.161 -3.418 3 talkingpointsmemo.com 0.211 0.149 -3.566 4 washingtonmonthly.com 0.197 0.140 -3.692 5 liberaloasis.com 0.168 0.119 -3.963 6 digbysblog.blogspot.com 0.167 0.118 -3.978 7 instapundit.com 0.160 0.113 -4.038 8 bodyandsoul.typepad.com 0.157 0.111 -4.065 9 pandagon.net 0.153 0.108 -4.106 10 talkleft.com 0.152 0.107 -4.115 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.020 Mean in random network: 0.595 Std.dev: 0.031 Std.dev in random network: 0.108 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): resource x resource
Rank Resource Value 1 dailykos.com 0.135 2 atrios.blogspot.com 0.132 3 talkingpointsmemo.com 0.122 4 washingtonmonthly.com 0.115 5 liberaloasis.com 0.098 6 digbysblog.blogspot.com 0.097 7 instapundit.com 0.093 8 bodyandsoul.typepad.com 0.091 9 pandagon.net 0.089 10 talkleft.com 0.088 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: resource x resource (size: 1490, density: 0.00856943)
Rank Resource Value Unscaled Context* 1 itlookslikethis.blogeasy.com 0.002 0.000 8.220 2 bushmisunderestimated.blogspot.com 0.002 0.000 8.220 3 etherealgirl.blogspot.com 0.002 0.000 8.220 4 michaelphillips.blogspot.com 0.002 0.000 8.220 5 lennonreport.blogspot.com 0.002 0.000 8.220 6 isdl.blogspot.com 0.002 0.000 8.220 7 isdl.weblogs.us 0.002 0.000 8.220 8 janm.blogspot.com 0.002 0.000 8.220 9 nerofiddled.blogspot.com 0.002 0.000 8.220 10 saveoursenate.blogspot.com 0.002 0.000 8.220 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.001 Mean in random network: 0.477 Std.dev: 0.001 Std.dev in random network: -0.058 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): resource x resource
Rank Resource Value Unscaled 1 etalkinghead.com 0.002 0.000 2 georgewbush.com 0.002 0.000 3 freerepublic.com 0.002 0.000 4 blog.johnkerry.com 0.002 0.000 5 gregpalast.com 0.002 0.000 6 andrewsullivan.com 0.002 0.000 7 right-thinking.com 0.002 0.000 8 moorewatch.com 0.002 0.000 9 politicalwire.com 0.002 0.000 10 smirkingchimp.com 0.002 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: resource x resource (size: 1490, density: 0.00856943)
Rank Resource Value Unscaled Context* 1 blogsforbush.com 0.099 218463.953 0.822 2 atrios.blogspot.com 0.041 90985.867 0.338 3 instapundit.com 0.034 76270.078 0.282 4 dailykos.com 0.025 54981.973 0.201 5 newleftblogs.blogspot.com 0.021 45895.516 0.166 6 madkane.com/notable.html 0.020 45021.613 0.163 7 wizbangblog.com 0.018 40602.738 0.146 8 lashawnbarber.com 0.016 36135.555 0.129 9 hughhewitt.com 0.015 34249.664 0.122 10 washingtonmonthly.com 0.015 32659.922 0.116 * Number of standard deviations from the mean of a random network of the same size and density
Mean: 0.001 Mean in random network: 0.001 Std.dev: 0.004 Std.dev in random network: 0.119 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): resource x resource
Rank Resource Value 1 politicalstrategy.org 0.200 2 madkane.com/notable.html 0.181 3 liberaloasis.com 0.179 4 stagefour.typepad.com/commonprejudice 0.175 5 bodyandsoul.typepad.com 0.173 6 corrente.blogspot.com 0.169 7 atrios.blogspot.com/ 0.166 8 newleftblogs.blogspot.com 0.161 9 tbogg.blogspot.com 0.161 10 atrios.blogspot.com 0.160 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): resource x resource
Rank Resource Value 1 dailykos.com 0.321 2 talkingpointsmemo.com 0.308 3 atrios.blogspot.com 0.301 4 washingtonmonthly.com 0.255 5 talkleft.com 0.207 6 juancole.com 0.203 7 instapundit.com 0.200 8 yglesias.typepad.com/matthew 0.193 9 pandagon.net 0.191 10 digbysblog.blogspot.com 0.188 Information centrality
Calculate the Stephenson and Zelen information centrality measure for each node.
Input network(s): resource x resource
Rank Resource Value Unscaled 1 blogsforbush.com 0.001 3.892 2 newleftblogs.blogspot.com 0.001 3.845 3 politicalstrategy.org 0.001 3.840 4 madkane.com/notable.html 0.001 3.839 5 cayankee.blogs.com 0.001 3.834 6 lashawnbarber.com 0.001 3.818 7 liberaloasis.com 0.001 3.817 8 presidentboxer.blogspot.com 0.001 3.817 9 techievampire.net/wppol 0.001 3.811 10 gevkaffeegal.typepad.com/the_alliance 0.001 3.809 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): resource x resource
Rank Resource Value 1 atrios.blogspot.com 26845.000 2 dailykos.com 18501.000 3 liberaloasis.com 17551.000 4 digbysblog.blogspot.com 15484.000 5 bodyandsoul.typepad.com 15378.000 6 washingtonmonthly.com 11915.000 7 instapundit.com 11760.000 8 pandagon.net 10542.000 9 talkingpointsmemo.com 10446.000 10 dneiwert.blogspot.com 10329.000 Simmelian ties
The normalized number of Simmelian ties of each node.
Input network(s): resource x resource
Rank Resource Value Unscaled 1 blogsforbush.com 0.066 99.000 2 atrios.blogspot.com 0.046 69.000 3 instapundit.com 0.036 53.000 4 bodyandsoul.typepad.com 0.032 48.000 5 tbogg.blogspot.com 0.032 47.000 6 lashawnbarber.com 0.030 44.000 7 corrente.blogspot.com 0.029 43.000 8 digbysblog.blogspot.com 0.028 42.000 9 liberaloasis.com 0.028 41.000 10 xnerg.blogspot.com 0.026 39.000 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): resource x resource
Rank Resource Value 1 quimundus.modblog.com 1.000 2 parabasis.typepad.com 0.563 3 thewritewing.blogspot.com 0.556 4 perryvsworld.blogspot.com 0.556 5 urbandemocracy.blogspot.com 0.520 6 angryhomo.blogspot.com 0.500 7 blog.glinka.com 0.500 8 cleancutkid.com 0.500 9 greendogdemocrat.blogspot.com 0.500 10 idiosyncratictendencies.com 0.500
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 blogsforbush.com itlookslikethis.blogeasy.com dailykos.com dailykos.com dailykos.com etalkinghead.com blogsforbush.com blogsforbush.com 2 atrios.blogspot.com bushmisunderestimated.blogspot.com atrios.blogspot.com atrios.blogspot.com instapundit.com georgewbush.com newleftblogs.blogspot.com dailykos.com 3 instapundit.com etherealgirl.blogspot.com talkingpointsmemo.com talkingpointsmemo.com talkingpointsmemo.com freerepublic.com madkane.com/notable.html instapundit.com 4 dailykos.com michaelphillips.blogspot.com washingtonmonthly.com washingtonmonthly.com atrios.blogspot.com blog.johnkerry.com politicalstrategy.org atrios.blogspot.com 5 newleftblogs.blogspot.com lennonreport.blogspot.com liberaloasis.com liberaloasis.com drudgereport.com gregpalast.com cayankee.blogs.com talkingpointsmemo.com 6 madkane.com/notable.html isdl.blogspot.com digbysblog.blogspot.com digbysblog.blogspot.com powerlineblog.com andrewsullivan.com liberaloasis.com washingtonmonthly.com 7 wizbangblog.com isdl.weblogs.us instapundit.com instapundit.com blogsforbush.com right-thinking.com lashawnbarber.com drudgereport.com 8 lashawnbarber.com janm.blogspot.com bodyandsoul.typepad.com bodyandsoul.typepad.com washingtonmonthly.com moorewatch.com gevkaffeegal.typepad.com/the_alliance powerlineblog.com 9 hughhewitt.com nerofiddled.blogspot.com pandagon.net pandagon.net michellemalkin.com politicalwire.com presidentboxer.blogspot.com michellemalkin.com 10 washingtonmonthly.com saveoursenate.blogspot.com talkleft.com talkleft.com truthlaidbear.com smirkingchimp.com corrente.blogspot.com hughhewitt.com