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arXiv 1902.02668physics.soc-phcs.SI
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部分二部网络的反模块性质使其成为次小世界

Anti-modular nature of partially bipartite networks makes them infra small-world

Aradhana Singh, Md. Izhar Ashraf, Sitabhra Sinha

摘要:

复杂系统中的强相互依赖性可以表现为部分二分网络,其特征在于主要发生在不同节点组(标识为模块)之间的相互作用。在本文中,我们证明了这种网络的反模特征,例如,由自然语言文本的语料库中字母字符的相邻出现所定义的那些可以导致显著的结构特性,这些结构特性将它们置于公知的规则/小世界/随机网络范例之外。使用集成的模型网络,其模块化可以调整,我们证明了强大的模块大小的异质性,在反模块化随机网络赋予他们更高的通信效率和较低的聚类比他们的随机同行,使他们的小世界。反模块化的通道与网络的频谱特性的特征变化相关联,包括由归一化拉普拉斯算子的主特征向量(PEV)表现出的离域过渡。这是伴随着出现突出双峰分布的PEV组件,它可以作为一个签名识别反模块化组织的经验网络。

英文摘要:

Strong inter-dependence in complex systems can manifest as partially bipartite networks characterized by interactions occurring primarily between distinct groups of nodes (identified as modules). In this paper, we show that the anti-modular character of such networks, e.g., those defined by the adjacent occurrence of alphabetic characters in corpora of natural language texts, can result in striking structural properties which place them outside the well-known regular/small-world/random network paradigm. Using an ensemble of model networks whose modularity can be tuned, we demonstrate that strong module size heterogeneity in anti-modular random networks imparts them with higher communication efficiency and lower clustering than their randomized counterparts, making them infra small-world. Passage to anti-modularity is associated with characteristic changes in spectral properties of the network, including a delocalization transition exhibited by the principal eigenvector (PEV) of the normalized Laplacian. This is accompanied by the emergence of prominent bimodality in the distribution of PEV components, which can function as a signature for identifying anti-modular organization in empirical networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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