Oggier Frédérique, Phetsouvanh Silivanxay, Datta Anwitaman
Division of Mathematical Sciences, Nanyang Technological University, Singapore, Singapore.
School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.
PeerJ Comput Sci. 2019 Sep 16;5:e220. doi: 10.7717/peerj-cs.220. eCollection 2019.
The notion of entropic centrality measures how central a node is in terms of how uncertain the destination of a flow starting at this node is: the more uncertain the destination, the more well connected and thus central the node is deemed. This implicitly assumes that the flow is indivisible, and at every node, the flow is transferred from one edge to another. The contribution of this paper is to propose a split-and-transfer flow model for entropic centrality, where at every node, the flow can actually be arbitrarily split across choices of neighbours. We show how to map this to an equivalent transfer entropic centrality set-up for the ease of computation, and carry out three case studies (an airport network, a cross-shareholding network and a Bitcoin transactions subnetwork) to illustrate the interpretation and insights linked to this new notion of centrality.
目的地越不确定，该节点就被认为连接性越好，因此也就越中心。这隐含地假设流是不可分割的，并且在每个节点处，流从一条边转移到另一条边。本文的贡献在于提出一种用于熵中心性的拆分与转移流模型，其中在每个节点处，流实际上可以在邻居的选择之间任意拆分。我们展示了如何将其映射到一个等效的转移熵中心性设置以便于计算，并进行了三个案例研究（一个机场网络、一个交叉持股网络和一个比特币交易子网）来说明与这种新的中心性概念相关的解释和见解。
