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  1. Computational and Mathematical Organization Theory
  2. Computational and Mathematical Organization Theory : Volume 12
  3. Computational and Mathematical Organization Theory : Volume 12, Issue 1, April 2006
  4. Identifying sets of key players in a social network
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Computational and Mathematical Organization Theory : Volume 23
Computational and Mathematical Organization Theory : Volume 22
Computational and Mathematical Organization Theory : Volume 21
Computational and Mathematical Organization Theory : Volume 20
Computational and Mathematical Organization Theory : Volume 19
Computational and Mathematical Organization Theory : Volume 18
Computational and Mathematical Organization Theory : Volume 17
Computational and Mathematical Organization Theory : Volume 16
Computational and Mathematical Organization Theory : Volume 15
Computational and Mathematical Organization Theory : Volume 14
Computational and Mathematical Organization Theory : Volume 13
Computational and Mathematical Organization Theory : Volume 12
Computational and Mathematical Organization Theory : Volume 12, Issue 4, December 2006
Computational and Mathematical Organization Theory : Volume 12, Issue 2-3, October 2006
Computational and Mathematical Organization Theory : Volume 12, Issue 1, April 2006
Introduction
Combating terrorist networks: An evolutionary approach
Identifying sets of key players in a social network
Using activity focus networks to pressure terrorist organizations
Destabilization of covert networks
Computational and Mathematical Organization Theory : Volume 11
Computational and Mathematical Organization Theory : Volume 10
Computational and Mathematical Organization Theory : Volume 9
Computational and Mathematical Organization Theory : Volume 8
Computational and Mathematical Organization Theory : Volume 7
Computational and Mathematical Organization Theory : Volume 6
Computational and Mathematical Organization Theory : Volume 5
Computational and Mathematical Organization Theory : Volume 4
Computational and Mathematical Organization Theory : Volume 3

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Identifying sets of key players in a social network

Content Provider SpringerLink
Author Borgatti, Stephen P.
Copyright Year 2006
Abstract A procedure is described for finding sets of key players in a social network. A key assumption is that the optimal selection of key players depends on what they are needed for. Accordingly, two generic goals are articulated, called KPP-POS and KPP-NEG. KPP-POS is defined as the identification of key players for the purpose of optimally diffusing something through the network by using the key players as seeds. KPP-NEG is defined as the identification of key players for the purpose of disrupting or fragmenting the network by removing the key nodes. It is found that off-the-shelf centrality measures are not optimal for solving either generic problem, and therefore new measures are presented.
Starting Page 21
Ending Page 34
Page Count 14
File Format PDF
ISSN 1381298X
Journal Computational and Mathematical Organization Theory
Volume Number 12
Issue Number 1
e-ISSN 15729346
Language English
Publisher Kluwer Academic Publishers
Publisher Date 2006-01-01
Publisher Place Boston
Access Restriction Subscribed
Subject Keyword Social networks Centrality Cohesion Artificial Intelligence (incl. Robotics) Management Operations Research/Decision Theory Methodology of the Social Sciences Sociology
Content Type Text
Resource Type Article
Subject Modeling and Simulation Applied Mathematics Computational Mathematics Computer Science Decision Sciences
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