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| | * ''强连通子图'': 任意两个节点间都存在有向路径的子图。 | | * ''强连通子图'': 任意两个节点间都存在有向路径的子图。 |
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| − | ===Node centrality===
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| − | {{Main|Centrality}}
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| − | Centrality indices produce rankings which seek to identify the most important nodes in a network model. Different centrality indices encode different contexts for the word "importance." The [[betweenness centrality]], for example, considers a node highly important if it form bridges between many other nodes. The [[Centrality#Eigenvector centrality|eigenvalue centrality]], in contrast, considers a node highly important if many other highly important nodes link to it. Hundreds of such measures have been proposed in the literature.
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| − | Centrality indices are only accurate for identifying the most central nodes. The measures are seldom, if ever, meaningful for the remainder of network nodes.
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| − | <ref name="Lawyer2015">
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| − | {{cite journal |last1= Lawyer |first1= Glenn |title= Understanding the spreading power of all nodes in a network| journal=Scientific Reports
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| − | |volume= 5 |pages= 8665 |date=March 2015
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| − | |number=O8665
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| − | | doi=10.1038/srep08665
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| − | |pmid= 25727453 |pmc= 4345333 |bibcode= 2015NatSR...5E8665L |arxiv=1405.6707}}
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| − | </ref>
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| − | <ref name="Sikic2013">
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| − | {{cite journal
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| − | |last1 = Sikic
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| − | |first1=Mile
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| − | |last2=Lancic
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| − | |first2=Alen
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| − | |last3= Antulov-Fantulin
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| − | |first3=Nino
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| − | |last4=Stefancic
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| − | |first4=Hrvoje
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| − | | title = Epidemic centrality -- is there an underestimated epidemic impact of network peripheral nodes?
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| − | | journal = European Physical Journal B
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| − | |date=October 2013
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| − | | volume = 86
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| − | | pages = 440
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| − | | number = 10
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| − | | doi=10.1140/epjb/e2013-31025-5
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| − | |arxiv=1110.2558
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| − | |bibcode=2013EPJB...86..440S
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| − | }}
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| − | </ref>
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| − | Also, their indications are only accurate within their assumed context for importance, and tend to "get it wrong" for other contexts.<ref name="Borgatti2005">
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| − | {{cite journal |last1= Borgatti |first1= Stephen P.|year= 2005 |title= Centrality and Network Flow |journal=Social Networks |volume= 27|issue= |pages= 55–71|doi=10.1016/j.socnet.2004.11.008 |url= |citeseerx= 10.1.1.387.419}}
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| − | </ref> For example, imagine two separate communities whose only link is an edge between the most junior member of each community. Since any transfer from one community to the other must go over this link, the two junior members will have high betweenness centrality. But, since they are junior, (presumably) they have few connections to the "important" nodes in their community, meaning their eigenvalue centrality would be quite low.
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| − | The concept of centrality in the context of static networks was extended, based on empirical and theoretical research, to dynamic centrality<ref name="dynamic1">{{cite journal | last1 = Braha | first1 = D. | last2 = Bar-Yam | first2 = Y. | year = 2006 | title = From Centrality to Temporary Fame: Dynamic Centrality in Complex Networks | url = | journal = Complexity | volume = 12 | issue = 2| pages = 59–63 | doi=10.1002/cplx.20156| arxiv = physics/0611295 | bibcode = 2006Cmplx..12b..59B }}</ref> in the context of time-dependent and temporal networks.<ref name="dynamic2">{{cite journal | last1 = Hill | first1 = S.A. | last2 = Braha | first2 = D. | year = 2010 | title = Dynamic Model of Time-Dependent Complex Networks | url = | journal = Physical Review E | volume = 82 | issue = 4| page = 046105 | doi=10.1103/physreve.82.046105| pmid = 21230343 | arxiv = 0901.4407 | bibcode = 2010PhRvE..82d6105H }}</ref><ref name="dynamic3">Gross, T. and Sayama, H. (Eds.). 2009. ''Adaptive Networks: Theory, Models and Applications.'' Springer.</ref><ref name="dynamic4">Holme, P. and Saramäki, J. 2013. ''Temporal Networks.'' Springer.</ref>
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| | ===节点中心性=== | | ===节点中心性=== |