论文标题
优先附件：多属性增长过程生成不同拓扑的无标度网络
Preferential attachment: a multi-attribute growth process generating scale-free networks of different topologies
论文作者
论文摘要
本文扩展了对优先依恋增长过程的基于程度的考虑，并应用了五个不同的连接标准（节点程度，聚类系数，中间性中心，紧密的中心性和特征向量中心性）来定义网络中新链接的发展。基于统计推断，分析表明，所有可用的控制属性都能够生成SF网络，而所提出的广义优先依恋增长过程在不同的控制属性下会产生统计上不同拓扑的网络，并且中心性是中心性的是控制 - 归因于更好地拓扑的网络。总体而言，本文介绍了优先依恋的多维概念化，该概念可以激发进一步的研究，并可以为现实世界网络的建模和解释提供新的工具，这些工具目前无法通过学位驱动的BA模型来充分解释。
This paper expands the degree-based consideration of the preferential attachment growth process and applies five different connectivity criteria (node degree, clustering coefficient, betweenness centrality, closeness centrality, and eigenvector centrality) to define the development of new links in the networks. Based on statistical inference, the analysis shows that all the available control attributes are capable generating SF networks, that the proposed generalized preferential attachment growth process produces networks of statistically different topologies, under different control-attributes, and that the betweenness centrality is the control-attribute generating networks of better topology. Overall, this paper introduces a multi-dimensional conceptualization of preferential attachment, which can motivate further research and can provide new tools for the modeling and interpretation of real-world networks that currently cannot be fully explained by the degree-driven BA models.
