These scripts implement several measures allowing to compare two community structures, i.e. two partitions of the node set of a given graph. They are based on popular measures defined in the field of cluster analysis, namely (see the source code for original bibliographic references): Purity (also known under many other names in the literature, such as percent correct, accuracy, etc.); Rand index and its adjusted version; Normalized mutual information. The scripts provided here implement (or show how to use existing implementations of) these classic measures, and also some modified versions. Those allow to take into account some weight defined for each one of the considered elements (in our case: nodes). The goal here is to be able to facto...
A network is said to exhibit community structure if the nodes of the network can be easily grouped i...
Clustering in graphs aims to group vertices with similar pat- terns of connections. Applications inc...
International audienceDetecting community structure discloses tremendous information about complex n...
Abstract. Community detection can be considered as a variant of cluster analysis applied to complex ...
International audienceCommunity detection is one of the most active fields in complex networks analy...
International audienceCommunity structure is of paramount importance for the understanding of comple...
Community structure is a commonly observed feature of real networks. The term refers to the presence...
International audienceReal world complex networks may contain hidden structures called communities o...
The R source code (based on the igraph library) for the measures described in this article is freely...
International audienceEvaluating a network partition just only via conventional quality metrics - su...
Abstract. Community detection is a very active field in complex networks analysis, consisting in ide...
Abstract. Community detection in networks is a broad problem with many proposed solutions. Existing ...
Determining the structure of large and complex networks is a problem that has stirred great interest...
Abstract. Clustering in graphs aims to group vertices with similar pat-terns of connections. Applica...
Community detection refers to extracting dense interacting nodes or subgraphs that form relevant agg...
A network is said to exhibit community structure if the nodes of the network can be easily grouped i...
Clustering in graphs aims to group vertices with similar pat- terns of connections. Applications inc...
International audienceDetecting community structure discloses tremendous information about complex n...
Abstract. Community detection can be considered as a variant of cluster analysis applied to complex ...
International audienceCommunity detection is one of the most active fields in complex networks analy...
International audienceCommunity structure is of paramount importance for the understanding of comple...
Community structure is a commonly observed feature of real networks. The term refers to the presence...
International audienceReal world complex networks may contain hidden structures called communities o...
The R source code (based on the igraph library) for the measures described in this article is freely...
International audienceEvaluating a network partition just only via conventional quality metrics - su...
Abstract. Community detection is a very active field in complex networks analysis, consisting in ide...
Abstract. Community detection in networks is a broad problem with many proposed solutions. Existing ...
Determining the structure of large and complex networks is a problem that has stirred great interest...
Abstract. Clustering in graphs aims to group vertices with similar pat-terns of connections. Applica...
Community detection refers to extracting dense interacting nodes or subgraphs that form relevant agg...
A network is said to exhibit community structure if the nodes of the network can be easily grouped i...
Clustering in graphs aims to group vertices with similar pat- terns of connections. Applications inc...
International audienceDetecting community structure discloses tremendous information about complex n...