DEEN: A Simple and Fast Algorithm for Network Community Detection

Abstract

Abstract. This paper introduces an algorithm for network community detection called DEEN (Delete Edges and Expand Nodes) consisting of two simple steps. First edges of the graph estimated to connect different clusters are detected and removed, next the resulting graph is used for generating communities by expanding seed nodes. DEEN uses as parameters the minimum and maximum allowed size of a cluster, and a resolution parameter whose value influences the number of removed edges. Application of DEEN to the budding yeast protein network for detecting functional protein complexes indicates its capability to identify clusters containing proteins with the same functional category, improving on MCL, a popular state-of-the-art method for functional protein complex detection. Moreover, application of DEEN to two popular benchmark networks results in the detection of accurate communities, substantiating the effectiveness of the proposed method in diverse domains.

High quality multi-core multi-level algorithm for community detection

“…The communities having number of nodes less than the minimum number required in a community, labels all the nodes in that community as non-community nodes. This idea of recursively deleting communities is along the same lines as the one used in Jancura et al (2012). The general schema for the algorithm is shown in Figure 1.…”