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KONECT > Networks > Wikipedia talk, German

Wikipedia talk, German

About this network

This is the communication network of the German Wikipedia. Nodes represent users of the German Wikipedia, and an edge from user A to user B denotes that user A wrote a message on the talk page of user B at a certain timestamp.

Network info

CodeTde
Category Communication
Data source https://zenodo.org/record/49561
Vertex type User
Edge type Message
FormatDirected: Edges are directed Directed
Edge weightsMultiple unweighted: Multiple edges are possible Multiple unweighted
Metadata Loops:  An edge may connect a node with itself LoopTimestamps:  Edges are annotated with a timestamps Timestamps
Size519,403 vertices (users)
Volume6,729,794 edges (messages)
Unique volume1,751,343 edges (messages)
Average degree (overall)25.914 edges / vertex
Fill6.4918 × 10–6 edges / vertex2
Maximum degree395,780 edges
Reciprocity22.4%
Size of LCC505,468 vertices
Size of LSCC69,121 vertices
Wedge count22,215,138,984
Claw count9.8392640052472300 × 1014
Triangle count9,554,210
Square count12,355,986,906
4-tour count187,711,464,036
Power law exponent (estimated) with dmin1.8110 (dmin = 11)
Gini coefficient91.7%
Relative edge distribution entropy76.3%
Assortativity–0.12477
Clustering coefficient0.129%
Diameter13 edges
90-percentile effective diameter3.75 edges
Mean shortest path length3.30 edges
Spectral norm22742.
Algebraic connectivity0.033983
Preferential attachment exponent0.60406 (ε = 2.3966)
Temporal distribution of the Wikipedia talk, German network
Temporal distribution
Edge multiplicity distribution of the Wikipedia talk, German network
Edge multiplicity distribution
Cumulative edge multiplicity distribution of the Wikipedia talk, German network
Cumulative edge multiplicity distribution
Degree distribution of the Wikipedia talk, German network
Degree distribution
Outdegree distribution of the Wikipedia talk, German network
Outdegree distribution
Indegree distribution of the Wikipedia talk, German network
Indegree distribution
Degree distribution of the Wikipedia talk, German network
Degree distribution
Outdegree distribution of the Wikipedia talk, German network
Outdegree distribution
Indegree distribution of the Wikipedia talk, German network
Indegree distribution
Degree distribution of the Wikipedia talk, German network
Degree distribution
Outdegree distribution of the Wikipedia talk, German network
Outdegree distribution
Indegree distribution of the Wikipedia talk, German network
Indegree distribution
Clustering coefficient distribution of the Wikipedia talk, German network
Clustering coefficient distribution
Distance distribution of the Wikipedia talk, German network
Distance distribution
Distance distribution on a logistic scale of the Wikipedia talk, German network
Distance distribution on a logistic scale
Top-k eigenvalues of A of the Wikipedia talk, German network
Top-k eigenvalues of A
Top-k eigenvalues of N of the Wikipedia talk, German network
Top-k eigenvalues of N
Top-k eigenvalues of L of the Wikipedia talk, German network
Top-k eigenvalues of L
Spectral distribution of the eigenvalues of A of the Wikipedia talk, German network
Spectral distribution of the eigenvalues of A
Spectral distribution of the eigenvalues of N of the Wikipedia talk, German network
Spectral distribution of the eigenvalues of N
Spectral distribution of the eigenvalues of L of the Wikipedia talk, German network
Spectral distribution of the eigenvalues of L
Cumulative spectral distribution of A of the Wikipedia talk, German network
Cumulative spectral distribution of A
Cumulative spectral distribution of N of the Wikipedia talk, German network
Cumulative spectral distribution of N
Cumulative spectral distribution of L of the Wikipedia talk, German network
Cumulative spectral distribution of L
Complex eigenvalues of the asymmetric adjacency matrix of the Wikipedia talk, German network
Complex eigenvalues of the asymmetric adjacency matrix

Downloads

TSV file:downloadwiki_talk_de.tar.bz2 (36.89 MiB)

References

[1] Wikipedia talk, german network dataset -- KONECT, October 2016. [ http ]
[2] Jun Sun, Jérôme Kunegis, and Steffen Staab. Predicting user roles in social networks using transfer learning with feature transformation. In Proc. ICDM Workshop on Data Mining in Networks, 2016.

BibTeX