CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies, and Algorithms

Overview

In this work, we presents three empirical patterns related to k-cores in real-world graphs and their applications to anomaly detection, streaming algorithm design, and influential spreaders identification.

Paper


Codes

CoreScope v1.0 [Github Repository] includes

Datasets

Name#Nodes#EdgesDegeneracySourceDownload
Social Networks (Unipartite)
Hamster1.86K12.6K20 KONECT Link
Email36.7K184K43 SNAP and CMU Link
Catster150K5.45M419 KONECT Link
YouTube1.13M2.99M51 SNAP and MPI-SWS Link
Flickr1.72M15.6M568 KONECT and MPI-SWS Link
Orkut3.07M117M253 SNAP and MPI-SWS Link
LiveJournal4.00M34.7M360 SNAP and MPI-SWS Link
Twitter41.7M1.20B2.49K KAIST Link
FriendSter65.6M1.81B304 KONECT Link
Web Graphs (Unipartite)
Stanford282K1.99M71 SNAP Link
NotreDame326K1.09M155 SNAP Link
Internet Topology (Unipartite)
Caida26.5K53.4K22 SNAP and CAIDA Link
Skitter1.70M11.1M111 SNAP and CAIDA Link
Citation Networks (Unipartite)
HepTh27.8K352K37 SNAP and Cornell Link
Patent3.77M16.5M64 SNAP and NBER Link

People