Twitter (MPI)

This asymmetric network contains Twitter follow data based on a snapshot taken in 2009. A node represents a user. A directed edge indicates that a user follows another user.


Internal nametwitter_mpi
NameTwitter (MPI)
Data source
AvailabilityDataset is available for download
Consistency checkCheck was not executed
Online social network
Dataset timestamp 2010
Node meaningUser
Edge meaningFollowing
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops
Snapshot Is a snapshot and likely to not contain all data


Size n =52,579,682
Volume m =1,963,263,821
Wedge count s =177,464,933,477,000
Triangle count t =55,428,217,664
Maximum degree dmax =3,691,240
Maximum outdegree d+max =779,958
Maximum indegree dmax =3,503,656
Average degree d =74.677 7
Size of LCC N =52,515,193
Diameter δ =18
50-Percentile effective diameter δ0.5 =3.151 81
90-Percentile effective diameter δ0.9 =4.052 51
Mean distance δm =3.615 64
Clustering coefficient c =0.000 937 000
Reciprocity y =0.355 691
Non-bipartivity bA =0.380 728


Degree distribution

Cumulative degree distribution

Spectral graph drawing based on the adjacency matrix

Hop distribution

Matrix decompositions plots



[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] Meeyoung Cha, Hamed Haddadi, Fabricio Benevenuto, and Krishna P. Gummadi. Measuring user influence in Twitter: The million follower fallacy. In Proc. Int. Conf. on Weblogs and Soc. Media, pages 10–17, 2010.