Tsallis entropy of complex networks

TL;DR

This paper introduces a novel approach using Tsallis entropy to quantify the complexity of networks, considering both structural properties and node relationships, with the entropy value influenced by node selection and the parameter q.

Contribution

It proposes a generalized Tsallis entropy-based method to measure network complexity, accounting for node importance and relationships, extending traditional entropy measures.

Findings

Complexity depends on network structure and node relationships.

Node selection influences entropy values.

The parameter q controls the focus on different node types.

Abstract

How complex of the complex networks has attracted many researchers to explore it. The entropy is an useful method to describe the degree of the $complex$ of the complex networks. In this paper, a new method which is based on the Tsallis entropy is proposed to describe the $complex$ of the complex networks. The results in this paper show that the complex of the complex networks not only decided by the structure property of the complex networks, but also influenced by the relationship between each nodes. In other word, which kinds of nodes are chosen as the main part of the complex networks will influence the value of the entropy of the complex networks. The value of q in the Tsallis entropy of the complex networks is used to decided which kinds of nodes will be chosen as the main part in the complex networks. The proposed Tsallis entropy of the complex networks is a generalised method to describe the property of the complex networks.