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Evaluating network centrality using entropy tools
Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
2016 (engelsk)Inngår i: XXXVI International Sunbelt Social Network Conference: Presentation and Poster Abstract, 2016, s. 195-196Konferansepaper, Oral presentation with published abstract (Annet vitenskapelig)
Abstract [en]

We recently introduced a new way of using statistical entropies to capture interdependencies among vertex and edge variables in multivariate networks. These entropies are used to systematically check for tendencies in the multidimensional variable set concerning redundancies, functional relationships, independencies and conditional independencies among different variable combinations. An important use of this technique is to apply it for selection of good summary measures of network structure. For instance, there are many alternative network statistics available for measuring centrality, and it is not always easy to decide which one is appropriate for a current application. In this presentation, we consider different centrality statistics among the variables in the analysis. By using univariate and multivariate entropies, we aim to find the centrality measure that is most relevant for the network property of interest. Throughout this presentation, we use John Padgett’s extended Florentine network data consisting of 87 families where the vertices as well as the edges have numerical or qualitative attributes defined on them. We create edge and vertex variables that capture network information via the most common centrality measures. The dependence structure of the variables is then explored by entropy analysis and it is determined which centrality measure is most appropriate for representing political, social or economic influence among the Florentine families. Further, we demonstrate how divergence measures can be used to indicate and test structural tendencies with respect to centrality in this network.

sted, utgiver, år, opplag, sider
2016. s. 195-196
HSV kategori
Forskningsprogram
statistik
Identifikatorer
URN: urn:nbn:se:su:diva-137007OAI: oai:DiVA.org:su-137007DiVA, id: diva2:1058263
Konferanse
XXXVI Sunbelt Social Network Conference INSNA, Newport Beach, CA, 5-10 April 2016
Tilgjengelig fra: 2016-12-20 Laget: 2016-12-20 Sist oppdatert: 2017-01-04bibliografisk kontrollert

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Utmatningsformat
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