Share your thoughts, 1 month free Claude Pro on usSee more
WorkDL logo mark

Fast unfolding of communities in large networks

About

We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2.6 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular networks. .

Vincent D. Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Etienne Lefebvre• 2008

Related benchmarks

TaskDatasetResultRank
Node ClusteringCora
NMI41.49
179
Node ClusteringCiteseer
NMI28.62
151
Paraphrase DetectionMRPC
Avg Accuracy61.33
89
ClusteringWine
ARI0.81
53
ClusteringFMNIST
ARI40
43
ClusteringDigits
ARI0.9
23
ClusteringBreast cancer
NMI38
15
Abstractive SummarizationXsum--
14
Graph CompressionMUTAG
Data Size (BPE)4.8
13
Graph CompressionPTC
Data (BPE)5.27
13
Showing 10 of 55 rows

Other info

Follow for update