A new fast algorithm for reproducing complex networks with community structure

TL;DR

This paper presents a novel fast algorithm for generating complex networks with community structures, addressing heterogeneity in node degrees and community sizes, and compares it to existing methods.

Contribution

The paper introduces a new efficient algorithm for creating complex networks with realistic heterogeneity and analyzes its advantages over previous algorithms.

Findings

The new algorithm is faster and more flexible in modeling heterogeneity.

It outperforms the Lancichinetti et al. algorithm in quality and efficiency.

The paper discusses specific application areas for both algorithms.

Abstract

In this paper, we introduce a new algorithm allowing for generation of networks with heterogeneity of both node degrees and community sizes. The quality and efficiency of the algorithm is analyzed and compared to the other, so far the most popular algorithm which was proposed by Lancichinetti et al. We discuss the advantages and shortcomings of both algorithms indicating the areas of their potential application.