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Combining Weighted Centrality and Network Clustering

In Social Network Analysis (SNA) centrality measures focus on activity (degree), information access (betweenness), distance to all the nodes (closeness), or popularity (pagerank). We introduce a new measure quantifying the distance of nodes to the network center. It is called weighted distance to nearest center (WDNC) and it is based on edge-weighted closeness (EWC), a weighted version of closeness. It combines elements of weighted centrality as well as clustering. The WDNC will be tested on two e-mail networks of the R community, one of the most important open source programs for statistical computing and graphics. We will find that there is a relationship between the WDNC and the formal organization of the R community. / Series: Research Report Series / Department of Statistics and Mathematics

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_fa9
Date January 2009
CreatorsBohn, Angela, Theußl, Stefan, Feinerer, Ingo, Hornik, Kurt, Mair, Patrick, Walchhofer, Norbert
PublisherDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypePaper, NonPeerReviewed
Formatapplication/pdf
Relationhttp://statmath.wu.ac.at/, http://epub.wu.ac.at/1466/

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