000 | 06930cam a22007338i 4500 | ||
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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.) |
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040 |
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049 | _aMAIN | ||
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_a302.3 _223 |
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_aMAT029000 _2bisacsh |
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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. |
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300 | _a1 online resource (xiv, 450 pages). | ||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bn _2rdamedia |
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338 |
_aonline resource _bnc _2rdacarrier |
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490 | 1 |
_aWiley series in computational and quantitative social science ; _v2 |
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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. |
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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. |
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588 | 0 | _aPrint version record and CIP data provided by publisher; resource not viewed. | |
650 | 0 |
_aSocial networks _xMathematical models. |
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650 | 0 |
_aSocial networks _xComputer simulation. |
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650 | 0 | 4 |
_aXarxes socials _xModels matemàtics. |
650 | 0 | 4 |
_aXarxes socials _xSimulació per ordinador. |
650 | 7 |
_aMATHEMATICS _xProbability & Statistics _xGeneral. _2bisacsh |
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650 | 7 |
_aPSYCHOLOGY _xSocial Psychology. _2bisacsh |
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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. |
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856 | 4 | 0 |
_uhttp://onlinelibrary.wiley.com/book/10.1002/9781118915370 _zWiley Online Library |
942 |
_2ddc _cBK |
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999 |
_c207666 _d207666 |