Livemocha

This is the social network of Livemocha, an online language learning community. The network is undirected and unweighted.

Metadata

CodeLM
Internal namelivemocha
NameLivemocha
Data sourcehttp://socialcomputing.asu.edu/datasets/Livemocha
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Online social network
Node meaningUser
Edge meaningFriendship
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops

Statistics

Size n =104,103
Volume m =2,193,083
Loop count l =0
Wedge count s =716,316,150
Claw count z =221,251,722,199
Cross count x =77,695,008,140,876
Triangle count t =3,361,651
Square count q =1,282,771,394
4-Tour count T4 =13,131,821,918
Maximum degree dmax =2,980
Average degree d =42.132 9
Fill p =0.000 404 728
Size of LCC N =104,103
Diameter δ =6
50-Percentile effective diameter δ0.5 =2.655 28
90-Percentile effective diameter δ0.9 =3.633 65
Median distance δM =3
Mean distance δm =3.207 24
Gini coefficient G =0.720 790
Balanced inequality ratio P =0.217 667
Relative edge distribution entropy Her =0.900 277
Power law exponent γ =1.382 85
Tail power law exponent γt =2.131 00
Degree assortativity ρ =−0.146 773
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.014 078 9
Spectral norm α =275.173
Algebraic connectivity a =0.169 934
Spectral separation 1[A] / λ2[A]| =1.254 40
Non-bipartivity bA =0.202 804
Normalized non-bipartivity bN =0.104 296
Algebraic non-bipartivity χ =0.169 925
Spectral bipartite frustration bK =0.001 008 27
Controllability C =21,504
Relative controllability Cr =0.206 565

Plots

Degree distribution

Cumulative degree distribution

Lorenz curve

Spectral distribution of the adjacency matrix

Spectral distribution of the normalized adjacency matrix

Spectral distribution of the Laplacian

Spectral graph drawing based on the adjacency matrix

Spectral graph drawing based on the Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Degree assortativity

Zipf plot

Hop distribution

Delaunay graph drawing

Clustering coefficient distribution

Average neighbor degree distribution

SynGraphy

Matrix decompositions plots

Downloads

References

[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] R. Zafarani and H. Liu. Social computing data repository at ASU, 2009. [ http ]