networkscience.wordpress.com
Defining the Clustering Coefficient | networkscience
https://networkscience.wordpress.com/2013/09/08/defining-the-clustering-coefficient
Blog by Jérôme Kunegis. Skip to primary content. Defining the Clustering Coefficient. Variant (1) Define the clustering coefficient c. Measure the clustering in a network and should therefore correlate highly, right? Well, no. Look at the following plot:. This plot shows the two clustering coefficients for networks in the Koblenz Network Collection. Each network is represented by a two or three-letter code. The X axis represents c. And the Y axis represents c. This plot needs some explanation. This i...
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Largest Network Dataset Ever Released – As Big As Facebook | networkscience
https://networkscience.wordpress.com/2013/11/16/largest-network-dataset-ever-released-as-big-as-facebook
Blog by Jérôme Kunegis. Skip to primary content. Largest Network Dataset Ever Released As Big As Facebook. Good news for the network analysis community: A new very large Web hyperlink dataset was recently released: the Web Data Commons Hyperlink Graph. Consisting of 3.56 billion pages and 129 billion hyperlinks connecting them! For comparison, the Facebook friendship graph is reported to include 1.26 billion nodes. Users) and 150 billion links. For another comparison, our own Koblenz Network Collection.
twitterresearcher.wordpress.com
Networks | Twitter Research
https://twitterresearcher.wordpress.com/resources/networks
My blog on my research on Twitter. To get new network analysis researchers started I recommend downloading a few of those really great collections of networks of all kind. Those have initially been collected here: http:/ forum.gephi.org/viewtopic.php? They provide an excellent access to already existing Twitter networks. You are also free to of course crawl your own twitter networks using my Twitterlyzer (Ruby on Rails framework) software or try Nodexl for beginners. Giorgio Agamben: Magic and Happiness.
networkscience.wordpress.com
Index of Complex Networks – The “Google for Networks” by University of Colorado Boulder | networkscience
https://networkscience.wordpress.com/2016/06/04/index-of-complex-networks-the-google-for-networks-by-university-of-colorado-boulder
Blog by Jérôme Kunegis. Skip to primary content. Index of Complex Networks The “Google for Networks” by University of Colorado Boulder. This week at the Conference on Network Science (NetSci 2016). Aaron Clauset from the University of Colorado Boulder unveiled the Index of Complex Networks. Assembling information about thousands of network datasets available online. They have about 3500 entries at the moment, with many more to come in the near future. What does this mean for the field of Network Science?
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kunegis | networkscience
https://networkscience.wordpress.com/author/kunegis
Blog by Jérôme Kunegis. Skip to primary content. Skip to secondary content. How to Pronounce German Vowels. The German language may be known for its many consonants, but what most learners have trouble with are in fact the vowels. The following chart gives a pretty much thorough account of the pronunciation of German vowels, in form of a flowchart. It will help you determine how to pronounce the vowels in a given word. Download chart as PDF. UPDATE: This is version 5 of the chart, as of 2017-02-17. No Th...
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No Hairball – The Graph Drawing Experiment | networkscience
https://networkscience.wordpress.com/2016/06/22/no-hairball-the-graph-drawing-experiment
Blog by Jérôme Kunegis. Skip to primary content. No Hairball The Graph Drawing Experiment. QUICKLINK TO THE EXPERIMENT. Many graph drawings look like a hairball. The larger a network is, the harder it is to visualize it. Most graph drawing algorithms produce a giant “hairball”, in which nodes and edges are hopelessly mixed up, leaving no way to discern any structure whatsoever. Here is an example:. This is from one of my own papers ( WWW 2009. Can we learn anything from this drawing? Show only a subset o...
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Plotting a Degree Distribution on the Command Line | networkscience
https://networkscience.wordpress.com/2014/08/28/plotting-a-degree-distribution-on-the-command-line
Blog by Jérôme Kunegis. Skip to primary content. Plotting a Degree Distribution on the Command Line. The following shell command plots a degree distribution in a log-log scale. It uses only standard unix commands:. INPUTFILE sed -re ‘/ %/d;s, s* S s*( S ).*$, 1,’ sort uniq -c sort -n sed -re ‘s, s*( S ).*$, 1,;s,.,#,g’ uniq -c sed -re ‘s, s*( S ).*, 1,;s,.,#,g’. 8216;s “ YouTube links. The file “out.youtube-links” can be downloaded from here. You don’t need a log() function to plot logarithmic axes.
wang115o.myweb.cs.uwindsor.ca
Hao Wang's Homepage,School of Computer Science,University of Windsor
http://www.wang115o.myweb.cs.uwindsor.ca/index.html
School of and Computer Science. Email: wang115o dot uwindsor dot ca. Visualization: Glorious 3D graphs. I am now a Master student of School of Computer Science at University of Windsor, under the supervision of Dr.Lu. I received my Bachelor Degree in China University of Geosciences 2011, collaborate with Professor zhanya Xu. At present, my interest focuses on social networks data mining and sampling. Also I am interested in Image Processing and Image Animation. Important papers in Data Mining.
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