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001 ocn890377884
003 OCoLC
005 20171026111321.0
006 m o d
007 cr |||||||||||
008 140909s2014 nju ob 001 0 eng
010 _a 2014036097
020 _a9781118915370
_q(electronic bk.)
020 _a1118915372
_q(electronic bk.)
020 _a9781118915363
_q(electronic bk.)
020 _a1118915364
_q(electronic bk.)
020 _z9781118915356
020 _z1118915356
020 _z9780470714522
_q(hardback)
020 _z0470714522
_q(hardback)
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035 _a(OCoLC)890377884
040 _aDLC
_beng
_erda
_epn
_cDLC
_dIDEBK
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049 _aMAIN
050 1 0 _aHM741
072 7 _aPSY
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_2bisacsh
082 0 0 _a302.3
_223
084 _aMAT029000
_2bisacsh
100 1 _aBatagelj, Vladimir,
_d1948-
245 1 0 _aUnderstanding large temporal networks and spatial networks : exploration, pattern searching, visualization and network evolution /
_cVladimir Batagelj, Patrick Doreian, Anuska Ferligo, Natasa Kejzar.
_h[electronic resource]
263 _a1411
264 1 _aHoboken :
_bWiley,
_c2014.
300 _a1 online resource (xiv, 450 pages).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bn
_2rdamedia
338 _aonline resource
_bnc
_2rdacarrier
490 1 _aWiley series in computational and quantitative social science ;
_v2
500 _aMachine generated contents note: Dedication Preface 1 Temporal and spatial networks 1.1 Modern social network analysis 1.2 Network sizes 1.3 Substantive concerns 1.4 Computational methods 1.5 Data for large temporal networks 1.6 Induction and deduction 2 Foundations of methods for large networks 2.1 Networks 2.2 Types of networks 2.3 Large networks 2.4 Strategies for analyzing large networks 2.5 Statistical network measures 2.6 Subnetworks 2.7 Connectivity properties of networks 2.8 Triangular and short cycle connectivities 2.9 Islands 2.10 Cores and generalized cores 2.11 Important vertices in networks 2.12 Transition to methods for large networks 3 Methods for large networks 3.1 Acyclic networks 3.2 SPC weights in acyclic networks 3.3 Probabilistic flow in acyclic network 3.4 Nonacyclic citation networks 3.5 Two-mode networks from data tables 3.6 Bibliographic networks 3.7 Weights 3.8 Pathfinder 3.9 Clustering, blockmodeling and community detection 3.10 Clustering symbolic data 3.11 Approaches to temporal networks 3.12 Levels of analysis 3.13 Transition to substantive part 4 Scientific citation and other bibliographic networks 4.1 The centrality citation network 4.2 Preliminary data analyses 4.3 Transforming a citation network into an acyclic network 4.4 The most important works 4.5 SPC weights 4.6 Line cuts 4.7 Line islands 4.8 Other relevant subnetworks for a bounded network 4.9 Collaboration networks 4.10 A brief look at the SNA literature SN5 networks 4.11 On the centrality and SNA collaboration networks 5 Citation patterns in a United States patent data 5.1 Patents 5.2 Supreme Court decisions regarding patents 5.3 The 1976-2006 patent data 5.4 Structural Variables through Time 5.5 Some patterns of technological development 5.6 Important Sub Networks 5.7 Citation Patterns 5.8 Comparing citation patterns for two time intervals 5.9 Summary and conclusions 6 The US Supreme Court Citation Network 6.1 Introduction 6.2 Cocited islands of Supreme Court decisions 6.3 A Native American Line Island 6.4 A 'Perceived Threats to Social Order' line island 6.5 Other perceived threats 6.6 The Dred Scott Decision 6.7 Further reflections on the Supreme Court citation network 7 Football as the world's game 7.1 A brief historical overview 7.2 Football clubs 7.3 Football players 7.4 Football in England 7.5 Player migrations 7.6 Institutional arrangements and the organization of football 7.7 Court rulings 7.8 Specific factors impacting football migration 7.9 Some arguments and propositions 7.10 Some preliminary results 7.11 Player ages when recruited to the EPL 7.12 A partial summary of results 8 Networks of player movements to the EPL 8.1 Success in the EPL 8.2 The overall presence of other countries in the EPL 8.3 Network flows of footballers between clubs to reach the EPL 8.4 Moves from EPL clubs 8.5 Moves solely within the EPL 8.6 All trails of footballers to the EPL 8.7 Summary and conclusions 9 Mapping Spatial Diversity in the United States of America 9.1 Mapping Nations as Spatial Units of the United States 9.2 Representing networks in space 9.3 Clustering with a relational constraint 9.4 Data for constrained spatial clustering 9.5 Clustering the US counties with a spatial relational constraint 9.6 Summary 10 On studying large networks 10.1 Substance 10.2 Methods, techniques and algorithms 10.3 Network data 10.4 Surprises and issues triggered by them 10.5 Future work 10.6 Two final comments Appendix: Data Documentation A.1 Bibliographic networks A.2 Patent data A.3 Supreme Court data A.4 Football Data A.5 The USA spatial county network References Person index Subject index.
504 _aIncludes bibliographical references and index.
520 _a"This book explores social mechanisms that drive network change and link them to computationally sound models of changing structure to detect patterns. This text identifies the social processes generating these networks and how networks have evolved"--
_cProvided by publisher.
520 _a"This book explores social mechanisms that drive network change and link them to computationally sound models of changing structure to detect patterns"--
_cProvided by publisher.
588 0 _aPrint version record and CIP data provided by publisher; resource not viewed.
650 0 _aSocial networks
_xMathematical models.
650 0 _aSocial networks
_xComputer simulation.
650 0 4 _aXarxes socials
_xModels matemàtics.
650 0 4 _aXarxes socials
_xSimulació per ordinador.
650 7 _aMATHEMATICS
_xProbability & Statistics
_xGeneral.
_2bisacsh
650 7 _aPSYCHOLOGY
_xSocial Psychology.
_2bisacsh
655 4 _aElectronic books.
655 4 _aLlibres electrònics.
655 0 _aElectronic books.
776 0 8 _iPrint version:
_aBatagelj, Vladimir, 1948-
_tUnderstanding large temporal networks and spatial networks.
_dHoboken : Wiley, 2014
_z9780470714522
_w(DLC) 2014019650
_w(OCoLC)875249345
830 0 _aWiley series in computational and quantitative social science ;
_v2.
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9781118915370
_zWiley Online Library
942 _2ddc
_cBK
999 _c207666
_d207666