Community detection in complex networks using Extremal Optimization

TL;DR

This paper introduces a new extremal optimization method for detecting community structures in complex networks, demonstrating superior performance and accuracy on both simulated and real-world data.

Contribution

The paper presents a novel extremal optimization algorithm that outperforms existing methods in identifying community structures in large complex networks.

Findings

Outperforms existing algorithms in modularity optimization

Effective on both simulated and real networks

Suitable for large-scale network analysis

Abstract

We propose a novel method to find the community structure in complex networks based on an extremal optimization of the value of modularity. The method outperforms the optimal modularity found by the existing algorithms in the literature. We present the results of the algorithm for computer simulated and real networks and compare them with other approaches. The efficiency and accuracy of the method make it feasible to be used for the accurate identification of community structure in large complex networks.