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In [[graph theory]] and [[network theory|network analysis]], indicators of '''centrality''' identify the most important [[vertex (graph theory)|vertices]] within a graph. Applications include identifying the most influential person(s) in a [[social network]], key infrastructure nodes in the [[Internet]] or [[urban network]]s, and [[super-spreader]]s of disease. Centrality concepts were first developed in [[social network analysis]], and many of the terms used to measure centrality reflect their [[sociology|sociological]] origin.<ref name="NewmanNetworks">Newman, M.E.J. 2010. ''Networks: An Introduction.'' Oxford, UK: Oxford University Press.</ref>

In [[graph theory]] and [[network theory|network analysis]], indicators of '''centrality''' identify the most important [[vertex (graph theory)|vertices]] within a graph. Applications include identifying the most influential person(s) in a [[social network]], key infrastructure nodes in the [[Internet]] or [[urban network]]s, and [[super-spreader]]s of disease. Centrality concepts were first developed in [[social network analysis]], and many of the terms used to measure centrality reflect their [[sociology|sociological]] origin.<ref name="NewmanNetworks">Newman, M.E.J. 2010. ''Networks: An Introduction.'' Oxford, UK: Oxford University Press.</ref>

In graph theory and network analysis, indicators of centrality identify the most important vertices within a graph. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, and super-spreaders of disease. Centrality concepts were first developed in , and many of the terms used to measure centrality reflect their sociological origin.

In graph theory and network analysis, indicators of centrality identify the most important vertices within a graph. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, and super-spreaders of disease. Centrality concepts were first developed in , and many of the terms used to measure centrality reflect their sociological origin.

They should not be confused with [[node influence metric]]s, which seek to quantify the influence of every node in the network.

They should not be confused with [[node influence metric]]s, which seek to quantify the influence of every node in the network.

They should not be confused with node influence metrics, which seek to quantify the influence of every node in the network.

They should not be confused with node influence metrics, which seek to quantify the influence of every node in the network.

在'''<font color="#ff8000">图论 graph theory </font>'''和'''<font color="#ff8000">网络分析 network analysis </font>'''中，'''<font color="#ff8000">中心性 centrality </font>'''指标用于识别图中最重要的顶点。其应用包括在社会网络中识别出最有影响力的个人，在因特网或城市网络中识别出最为关键的基础设施节点，以及识别疾病的超级传播者。中心性的概念最初由'''<font color="#ff8000">社会网络分析 social network analysis</font>'''所发展，因此许多用于衡量中心性的术语都反映出了它们的社会学出身。中心性不应与节点影响度相混淆，后者意在量化网络中每个节点的影响。

在'''<font color="#ff8000">图论 graph theory </font>'''和'''<font color="#ff8000">网络分析 network analysis </font>'''中，'''<font color="#ff8000">中心性 centrality </font>'''指标用于识别图中最重要的顶点。其应用包括在社会网络中识别出最有影响力的个人，在因特网或城市网络中识别出最为关键的基础设施节点，以及识别疾病的超级传播者。中心性的概念最初由'''<font color="#ff8000">社会网络分析 social network analysis</font>'''所发展，因此许多用于衡量中心性的术语都反映出了它们的社会学出身。<ref name="NewmanNetworks">Newman, M.E.J. 2010. ''Networks: An Introduction.'' Oxford, UK: Oxford University Press.</ref>中心性不应与节点影响度相混淆，后者意在量化网络中每个节点的影响。

==中心性指数的定义与特性Definition and characterization of centrality indices==

==中心性指数的定义与特性Definition and characterization of centrality indices==