Analysis of network by generalized mutual entropies

TL;DR

This paper introduces a generalized mutual entropy measure for analyzing complex networks, demonstrating its application on simulated scale-free and random networks, and discussing potential real-world applications.

Contribution

It proposes a novel generalized mutual entropy method for network analysis and tests its effectiveness on simulated network models.

Findings

Effective differentiation of network types using entropy measures

Potential for analyzing real-world complex networks

Applicability to various network structures

Abstract

Generalized mutual entropy is defined for networks and applied for analysis of complex network structures. The method is tested for the case of computer simulated scale free networks, random networks, and their mixtures. The possible applications for real network analysis are discussed.