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Combining Weighted Centrality and Network Clustering

Bohn, Angela and Theußl, Stefan and Feinerer, Ingo and Hornik, Kurt and Mair, Patrick and Walchhofer, Norbert (2009) Combining Weighted Centrality and Network Clustering. Research Report Series / Department of Statistics and Mathematics, 97. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.

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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.

Item Type: Paper
Keywords: social network analysis / centrality measure / closeness / clustering / R-help
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 09 Dec 2009 20:13
Last Modified: 24 Feb 2017 14:14
URI: http://epub.wu.ac.at/id/eprint/1466


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