Networks:
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Oxford
Oxford University Press
2018
|
Ausgabe: | Second edition |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke Literaturverzeichnis: Seite 732-750 |
Beschreibung: | xi, 780 Seiten Illustrationen, Diagramme |
ISBN: | 9780198805090 |
Internformat
MARC
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245 | 1 | 0 | |a Networks |c Mark Newman, University of Michigan |
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264 | 1 | |a Oxford |b Oxford University Press |c 2018 | |
300 | |a xi, 780 Seiten |b Illustrationen, Diagramme | ||
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Datensatz im Suchindex
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adam_text |
Contents Preface ix 1 Introduction 1 1 The empirical study of networks 13 2 Technological networks 2.1 The Internet. 2.2 The telephone network. 2.3 Power grids . 2.4 Transportation networks. 2.5 Delivery and distribution networks. 14 15 25 27 28 29 3 Networks of information 3.1 The World Wide Web. 3.2 Citation networks. 3.3 Other information networks. 32 32 37 41 4 Social networks 4.1 The empirical study of social networks. 4.2 Interviews and questionnaires. 4.3 Direct observation. 4.4 Data from archival or third-party records. 4.5 Affiliation networks. 4.6 The small-world experiment. 4.7 Snowball sampling, contact tracing, and random walks . 47 47 51 57 58 60 62 65 5 Biological networks 5.1 Biochemical networks. 5.2 Networks in the
brain. 5.3 Ecological networks. 70 70 88 95 v
Contents II Fundamentals of network theory 6 103 Mathematics of networks 105 6.1 Networks and their representation. 105 6.2 The adjacency matrix. 106 6.3 Weighted networks. 108 6.4 Directed networks. 110 6.5 Hypergraphs. 114 6.6 Bipartite networks. 115 6.7 Multilayer and dynamic networks. 118 6.8 Trees . 121 6.9 Planar networks. 123 6.10 Degree. 126 6.11 Walks and paths. 131 6.12 Components. 133 6.13 Independent paths, connectivity, and cut sets. 137 6.14 The graph Laplacian. 142 7 Measures and metrics 7.1 7.2 7.3 7.4 7.5 7.6 7.7 8 Computer algorithms 8.1 8.2 8.3 8.4 8.5 8.6 8.7 9 218 Software for network analysis and visualization
.219 Running time and computational complexity.221 Storing network data. 225 Algorithms for basic network quantities. 237 Shortest paths and breadth-first search. 241 Shortest paths in networks with varying edge lengths.257 Maximum flows and minimum cuts.262 Network statistics and measurement error 9.1 9.2 9.3 9.4 vi 158 Centrality. 159 Groups of nodes. 177 Transitivity and the clustering coefficient . 183 Reciprocity. 189 Signed edges and structural balance. 190 Similarity. 194 Homophily and assortative mixing.201 275 Types of error. 276 Sources of error. 278 Estimating errors. 281 Correcting
errors. 297
Contents 10 The structure of real-world networks 304 10.1 Components.304 10.2 Shortest paths and the small-world effect . 310 10.3 Degree distributions . 313 10.4 Power laws and scale-free networks.317 10.5 Distributions of other centrality measures. 330 10.6 Clustering coefficients . 332 10.7 Assortative mixing.335 III Network models 341 11 Random graphs 342 11.1 Random graphs. 343 11.2 Mean number of edges and mean degree . 345 11.3 Degree distribution.346 11.4 Clustering coefficient.347 11.5 Giant component. 347 11.6 Small components. 355 11.7 Path lengths.360 11.8 Problems with the random graph.364 12 The configuration model 369 12.1 The configuration
model.370 12.2 Excess degree distribution. 377 12.3 Clustering coefficient.381 12.4 Locally tree-like networks. 382 12.5 Number of second neighbors of a node. 383 12.6 Giant component. 384 12.7 Small components. 391 12.8 Networks with power-law degree distributions. 395 12.9 Diameter.399 12.10 Generating function methods. 401 12.11 Other random graph models. 416 13 Models of network formation 434 13.1 Preferential attachment.435 13.2 The model of Barabási and Albert. 448 13.3 Time evolution of the network and the first mover effect . 451 13.4 Extensions of preferential attachment models. 458 13.5 Node copying models.472 13.6 Network optimization models. 479 vii
Contents IV Applications 493 14 Community structure 494 14.1 14.2 14.3 14.4 14.5 14.6 14.7 Dividing networks into groups. 495 Modularity maximization.498 Methods based on information theory.515 Methods based on statistical inference.520 Other algorithms for community detection. 529 Measuring algorithm performance.538 Detecting other kinds of network structure . 551 15 Percolation and network resilience 15.1 15.2 15.3 15.4 15.5 569 Percolation.569 Uniform random removal of nodes.571 Non-uniform removal of nodes. 586 Percolation in real-world networks.593 Computer algorithms for percolation.594 16 Epidemics on networks 16.1 16.2 16.3 16.4 16.5 16.6 16.7 607 Models of the spread of infection. 608 Epidemic models on networks. 624 Outbreak sizes and percolation. 625 Time-dependent properties of epidemics on networks. 645 Time-dependent properties of the SI
model. 646 Time-dependent properties of the SIR model. 660 Time-dependent properties of the SIS model . 667 17 Dynamical systems on networks 17.1 17.2 17.3 17.4 17.5 675 Dynamical systems. 676 Dynamics on networks.685 Dynamics with more than one variable per node.694 Spectra of networks. 698 Synchronization. 701 18 Network search 18.1 18.2 18.3 viii 710 Web search. 710 Searching distributed databases. 713 Sending messages. 718 References 732 Index 751 |
any_adam_object | 1 |
author | Newman, Mark E. J. |
author_GND | (DE-588)133013073 |
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author_sort | Newman, Mark E. J. |
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classification_tum | DAT 250f MAT 904f |
ctrlnum | (OCoLC)1047376582 (DE-599)HBZHT019647081 |
discipline | Informatik Soziologie Mathematik Wirtschaftswissenschaften |
edition | Second edition |
format | Book |
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id | DE-604.BV044985341 |
illustrated | Illustrated |
indexdate | 2024-12-05T17:00:54Z |
institution | BVB |
isbn | 9780198805090 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030377658 |
oclc_num | 1047376582 |
open_access_boolean | |
owner | DE-91G DE-BY-TUM DE-11 DE-188 DE-19 DE-BY-UBM DE-M347 DE-83 DE-355 DE-BY-UBR DE-739 DE-20 DE-92 DE-703 |
owner_facet | DE-91G DE-BY-TUM DE-11 DE-188 DE-19 DE-BY-UBM DE-M347 DE-83 DE-355 DE-BY-UBR DE-739 DE-20 DE-92 DE-703 |
physical | xi, 780 Seiten Illustrationen, Diagramme |
publishDate | 2018 |
publishDateSearch | 2018 |
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publisher | Oxford University Press |
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spelling | Newman, Mark E. J. Verfasser (DE-588)133013073 aut Networks Mark Newman, University of Michigan Second edition Oxford Oxford University Press 2018 xi, 780 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderte Nachdrucke Literaturverzeichnis: Seite 732-750 Soziales Netzwerk (DE-588)4055762-5 gnd rswk-swf Graphentheorie (DE-588)4113782-6 gnd rswk-swf Rechnernetz (DE-588)4070085-9 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Netzwerktheorie (DE-588)4171531-7 gnd rswk-swf Netzwerk (DE-588)4171529-9 gnd rswk-swf Netzwerk (DE-588)4171529-9 s Rechnernetz (DE-588)4070085-9 s Mathematisches Modell (DE-588)4114528-8 s Graphentheorie (DE-588)4113782-6 s DE-604 Soziales Netzwerk (DE-588)4055762-5 s Netzwerktheorie (DE-588)4171531-7 s Erscheint auch als Online-Ausgabe 978-0-19-184323-5 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030377658&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Newman, Mark E. J. Networks Soziales Netzwerk (DE-588)4055762-5 gnd Graphentheorie (DE-588)4113782-6 gnd Rechnernetz (DE-588)4070085-9 gnd Mathematisches Modell (DE-588)4114528-8 gnd Netzwerktheorie (DE-588)4171531-7 gnd Netzwerk (DE-588)4171529-9 gnd |
subject_GND | (DE-588)4055762-5 (DE-588)4113782-6 (DE-588)4070085-9 (DE-588)4114528-8 (DE-588)4171531-7 (DE-588)4171529-9 |
title | Networks |
title_auth | Networks |
title_exact_search | Networks |
title_full | Networks Mark Newman, University of Michigan |
title_fullStr | Networks Mark Newman, University of Michigan |
title_full_unstemmed | Networks Mark Newman, University of Michigan |
title_short | Networks |
title_sort | networks |
topic | Soziales Netzwerk (DE-588)4055762-5 gnd Graphentheorie (DE-588)4113782-6 gnd Rechnernetz (DE-588)4070085-9 gnd Mathematisches Modell (DE-588)4114528-8 gnd Netzwerktheorie (DE-588)4171531-7 gnd Netzwerk (DE-588)4171529-9 gnd |
topic_facet | Soziales Netzwerk Graphentheorie Rechnernetz Mathematisches Modell Netzwerktheorie Netzwerk |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030377658&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT newmanmarkej networks |