关于网络参与的信息论表述

IF 2.6 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Physics Complexity Pub Date : 2024-03-27 DOI:10.1088/2632-072x/ad32da
Pavle Cajic, Dominic Agius, Oliver M Cliff, James M Shine, Joseph T Lizier, Ben D Fulcher
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引用次数: 0

摘要

参与系数是一个广泛使用的指标,用来衡量一个节点相对于网络模块分区的连接多样性。这种连接多样性概念的信息论表述(在此称为参与熵)是节点连接邻居的模块标签分布的香农熵。虽然其他文献已经对多样性度量进行了理论研究,包括生态学中的物种多样性指数,但其中许多结果以前都没有应用到网络中。在这里,我们证明了参与系数是参与熵的一阶近似值,并利用熵的理想加法特性,开发了网络中节点多重标签的连接多样性新指标,即联合参与熵和条件参与熵。这里提出的信息论形式主义允许研究复杂网络中新的、更微妙类型的节点连接模式。
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On the information-theoretic formulation of network participation
The participation coefficient is a widely used metric of the diversity of a node’s connections with respect to a modular partition of a network. An information-theoretic formulation of this concept of connection diversity, referred to here as participation entropy, has been introduced as the Shannon entropy of the distribution of module labels across a node’s connected neighbors. While diversity metrics have been studied theoretically in other literatures, including to index species diversity in ecology, many of these results have not previously been applied to networks. Here we show that the participation coefficient is a first-order approximation to participation entropy and use the desirable additive properties of entropy to develop new metrics of connection diversity with respect to multiple labelings of nodes in a network, as joint and conditional participation entropies. The information-theoretic formalism developed here allows new and more subtle types of nodal connection patterns in complex networks to be studied.
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来源期刊
Journal of Physics Complexity
Journal of Physics Complexity Computer Science-Information Systems
CiteScore
4.30
自引率
11.10%
发文量
45
审稿时长
14 weeks
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