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第745行： − 中心性度量 − *'''度中心性'''是指网络中节点的
→Centrality measures
===Centrality measures===
===Centrality measures===
Information about the relative importance of nodes and edges in a graph can be obtained through [[centrality]] measures, widely used in disciplines like [[sociology]]. Centrality measures are essential when a network analysis has to answer questions such as: "Which nodes in the network should be targeted to ensure that a message or information spreads to all or most nodes in the network?" or conversely, "Which nodes should be targeted to curtail the spread of a disease?". Formally established measures of centrality are [[degree centrality]], [[closeness centrality]], [[betweenness centrality]], [[eigenvector centrality]], and [[katz centrality]]. The objective of network analysis generally determines the type of centrality measure(s) to be used.<ref name="Wasserman_Faust"/>
Information about the relative importance of nodes and edges in a graph can be obtained through [[centrality]] measures, widely used in disciplines like [[sociology]]. Centrality measures are essential when a network analysis has to answer questions such as: "Which nodes in the network should be targeted to ensure that a message or information spreads to all or most nodes in the network?" or conversely, "Which nodes should be targeted to curtail the spread of a disease?". Formally established measures of centrality are [[degree centrality]], [[closeness centrality]], [[betweenness centrality]], [[eigenvector centrality]], and [[katz centrality]]. The objective of network analysis generally determines the type of centrality measure(s) to be used.<ref name="Wasserman_Faust"/>
*'''Degree centrality''' of a node in a network is the number of links (vertices) incident on the node.
*'''Degree centrality''' of a node in a network is the number of links (vertices) incident on the node.
*'''Closeness centrality''' determines how "close" a node is to other nodes in a network by measuring the sum of the shortest distances (geodesic paths) between that node and all other nodes in the network.
*'''Closeness centrality''' determines how "close" a node is to other nodes in a network by measuring the sum of the shortest distances (geodesic paths) between that node and all other nodes in the network.