Centrality Indices
Identifieur interne : 001916 ( Main/Merge ); précédent : 001915; suivant : 001917Centrality Indices
Auteurs : Dirk Koschützki [Allemagne] ; Katharina Anna Lehmann [Allemagne] ; Leon Peeters [Suisse] ; Stefan Richter [Allemagne] ; Dagmar Tenfelde-Podehl [Allemagne] ; Oliver Zlotowski [Allemagne]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2005.
Abstract
Abstract: Centrality indices are to quantify an intuitive feeling that in most networks some vertices or edges are more central than others. Many vertex centrality indices were introduced for the first time in the 1950s: e.g., the Bavelas index [50, 51], degree centrality [483] or a first feedback centrality, introduced by Seeley [510]. These early centralities raised a rush of research in which manifold applications were found. However, not every centrality index was suitable to every application, so with time, dozens of new centrality indices were published. This chapter will present some of the more influential, ‘classic’ centrality indices. We do not strive for completeness, but hope to give a catalog of basic centrality indices with some of their main applications.
Url:
DOI: 10.1007/978-3-540-31955-9_3
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sort="Tenfelde Podehl, Dagmar" uniqKey="Tenfelde Podehl D" first="Dagmar" last="Tenfelde-Podehl">Dagmar Tenfelde-Podehl</name><affiliation wicri:level="4"><country xml:lang="fr">Allemagne</country><wicri:regionArea>Department of Mathematics, Technische Universität Kaiserslautern, 67653, Kaiserslautern</wicri:regionArea><placeName><region type="land" nuts="2">Rhénanie-Palatinat</region><settlement type="city">Kaiserslautern</settlement></placeName><orgName type="university">Université technique de Kaiserslautern</orgName></affiliation></author><author><name sortKey="Zlotowski, Oliver" sort="Zlotowski, Oliver" uniqKey="Zlotowski O" first="Oliver" last="Zlotowski">Oliver Zlotowski</name><affiliation wicri:level="1"><country xml:lang="fr">Allemagne</country><wicri:regionArea>Algorithms and Data Structures, Univeristät Trier, 54296, Trier</wicri:regionArea><wicri:noRegion>54296, Trier</wicri:noRegion><wicri:noRegion>Trier</wicri:noRegion></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2005</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">E47931503AB6A57F6C51537FFCCB7C53ACBFDD77</idno><idno type="DOI">10.1007/978-3-540-31955-9_3</idno><idno type="ChapterID">3</idno><idno type="ChapterID">Chap3</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Centrality indices are to quantify an intuitive feeling that in most networks some vertices or edges are more central than others. 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