作为中心性度量的潜在增益

P. D. Meo, M. Levene, A. Provetti
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引用次数: 3

摘要

通航性是与人工或自然系统相关的图形的独特特征,其主要目标是信息或货物的运输。当代理能够通过本地路由决策有效地到达G中的任何目标节点时,我们说图G是可导航的。在社交网络中,可导航性转化为通过个人联系达到个人的能力。图的可导航性已经得到了很好的研究,但一个基本问题仍然存在:为什么有些人比其他人更有可能通过短的、朋友的朋友的交流链联系到他们?在本文中,我们通过提出一种称为潜在增益的新颖中心性度量来回答上述问题,该度量在非正式意义上量化了到达目标节点的容易程度。我们定义了势增益的两种变体,称为几何势增益和指数势增益,并给出了计算它们的快速算法。几何增益和潜在增益是一类新型复合中心性度量的第一个实例,即将G中节点的受欢迎程度与其与所有其他节点的相似性结合起来的中心性度量。正如之前的研究所示,流行度和相似性是规范人们在维基百科等大型网络中寻找信息的两个主要标准。我们给出了一个正式的证明,即节点的潜在增益总是等于它的度中心性(捕获流行度)和它的Katz中心性(捕获相似性)的乘积。•信息系统→网络爬行;Web索引。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential Gain as a Centrality Measure
Navigability is a distinctive features of graphs associated with artificial or natural systems whose primary goal is the transportation of information or goods. We say that a graph G is navigable when an agent is able to efficiently reach any target node in G by means of local routing decisions. In a social network navigability translates to the ability of reaching an individual through personal contacts. Graph navigability is well-studied, but a fundamental question is still open: why are some individuals more likely than others to be reached via short, friend-of-a-friend, communication chains? In this article we answer the question above by proposing a novel centrality metric called the potential gain, which, in an informal sense, quantifies the easiness at which a target node can be reached. We define two variants of the potential gain, called the geometric and the exponential potential gain, and present fast algorithms to compute them. The geometric and the potential gain are the first instances of a novel class of composite centrality metrics, i.e., centrality metrics which combine the popularity of a node in G with its similarity to all other nodes. As shown in previous studies, popularity and similarity are two main criteria which regulate the way humans seek for information in large networks such as Wikipedia. We give a formal proof that the potential gain of a node is always equivalent to the product of its degree centrality (which captures popularity) and its Katz centrality (which captures similarity). CCS CONCEPTS • Information systems → Web crawling; Web indexing.
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