Finding compact communities in large graphs

TL;DR

This paper introduces an efficient hierarchical clustering algorithm for detecting the connected core of communities in large graphs, emphasizing compactness and improved cluster quality.

Contribution

It proposes a novel approach combining LexDFS with a new compactness measure to identify core communities efficiently in large-scale graphs.

Findings

Creates highly compact clusters

Operates in O(n log n) time complexity

Effective in large graph community detection

Abstract

This article presents an efficient hierarchical clustering algorithm that solves the problem of core community detection. It is a variant of the standard community detection problem in which we are particularly interested in the connected core of communities. To provide a solution to this problem, we question standard definitions on communities and provide alternatives. We also propose a function called compactness, designed to assess the quality of a solution to this problem. Our algorithm is based on a graph traversal algorithm, the LexDFS. The time complexity of our method is in $O(n\times log(n))$. Experiments show that our algorithm creates highly compact clusters.