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KONECT > Networks > Wikipedia talk, Italian

Wikipedia talk, Italian

About this network

This is the communication network of the Italian Wikipedia. Nodes represent users of the Italian 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

CodeTit
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
Size863,846 vertices (users)
Volume3,067,680 edges (messages)
Unique volume1,661,453 edges (messages)
Average degree (overall)7.1024 edges / vertex
Fill2.2265 × 10–6 edges / vertex2
Maximum degree388,889 edges
Reciprocity17.4%
Size of LCC862,214 vertices
Size of LSCC36,356 vertices
Wedge count111,830,205,348
Claw count1.1983312889964536 × 1016
Triangle count3,355,399
Square count6,154,887,250
4-tour count496,562,923,582
Power law exponent (estimated) with dmin1.7910 (dmin = 30)
Gini coefficient83.3%
Relative edge distribution entropy68.2%
Assortativity–0.30142
Clustering coefficient0.00900%
Diameter7 edges
90-percentile effective diameter3.67 edges
Mean shortest path length3.05 edges
Spectral norm9318.4
Algebraic connectivity0.10277
Preferential attachment exponent0.46893 (ε = 1.5719)
Temporal distribution of the Wikipedia talk, Italian network
Temporal distribution
Edge multiplicity distribution of the Wikipedia talk, Italian network
Edge multiplicity distribution
Cumulative edge multiplicity distribution of the Wikipedia talk, Italian network
Cumulative edge multiplicity distribution
Degree distribution of the Wikipedia talk, Italian network
Degree distribution
Outdegree distribution of the Wikipedia talk, Italian network
Outdegree distribution
Indegree distribution of the Wikipedia talk, Italian network
Indegree distribution
Degree distribution of the Wikipedia talk, Italian network
Degree distribution
Outdegree distribution of the Wikipedia talk, Italian network
Outdegree distribution
Indegree distribution of the Wikipedia talk, Italian network
Indegree distribution
Degree distribution of the Wikipedia talk, Italian network
Degree distribution
Outdegree distribution of the Wikipedia talk, Italian network
Outdegree distribution
Indegree distribution of the Wikipedia talk, Italian network
Indegree distribution
Clustering coefficient distribution of the Wikipedia talk, Italian network
Clustering coefficient distribution
Distance distribution of the Wikipedia talk, Italian network
Distance distribution
Distance distribution on a logistic scale of the Wikipedia talk, Italian network
Distance distribution on a logistic scale
Top-k eigenvalues of A of the Wikipedia talk, Italian network
Top-k eigenvalues of A
Top-k eigenvalues of N of the Wikipedia talk, Italian network
Top-k eigenvalues of N
Top-k eigenvalues of L of the Wikipedia talk, Italian network
Top-k eigenvalues of L
Spectral distribution of the eigenvalues of A of the Wikipedia talk, Italian network
Spectral distribution of the eigenvalues of A
Spectral distribution of the eigenvalues of N of the Wikipedia talk, Italian network
Spectral distribution of the eigenvalues of N
Spectral distribution of the eigenvalues of L of the Wikipedia talk, Italian network
Spectral distribution of the eigenvalues of L
Cumulative spectral distribution of A of the Wikipedia talk, Italian network
Cumulative spectral distribution of A
Cumulative spectral distribution of N of the Wikipedia talk, Italian network
Cumulative spectral distribution of N
Cumulative spectral distribution of L of the Wikipedia talk, Italian network
Cumulative spectral distribution of L

Downloads

TSV file:downloadwiki_talk_it.tar.bz2 (17.60 MiB)

References

[1] Wikipedia talk, italian 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