A guide to temporal networks:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New Jersey
World Scientific
[2016]
|
| Series: | Series on complexity science
vol. 4 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xii, 237 Seiten Illustrationen |
| ISBN: | 9781786341143 |
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MARC
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Record in the Search Index
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| adam_text | Contents
Preface v
Acknowledgments vii
1. Introduction 1
2. Mathematical toolbox 7
2.1 Probability................................................ 7
2.1.1 Discrete variables.................................. 7
2.1.2 Continuous variables............................... 10
2.2 Renewal processes......................................... 11
2.2.1 Poisson processes.................................. 11
2.2.2 General renewal processes ......................... 15
2.3 Random walks and diffusion................................ 18
2.3.1 Discrete time...................................... 18
2.3.2 Continuous time.................................... 19
2.4 Power-law distributions................................... 21
2.5 Maximum likelihood........................................ 25
2.6 Entropy, information and similarity measures.............. 26
2.7 Matrix algebra............................................ 28
2.8 Linear stability.......................................... 30
2.9 Markov chains ............................................ 31
2.10 Branching processes....................................... 33
3. Static networks 37
3.1 Definition................................................ 37
3.2 Degree distribution....................................... 39
ix
X
A Guide to Temporal Networks
3.3 Measures derived from walks and paths ................. 41
3.4 Clustering coefficient................................. 43
3.5 Spectral properties...................................... 43
3.6 Discrete-time random walks on networks................... 46
3.7 Centrality............................................... 48
3.7.1 Closeness centrality.............................. 49
3.7.2 Betweenness centrality............................ 49
3.7.3 Katz centrality................................... 49
3.7.4 PageRank.......................................... 50
3.8 Models of networks....................................... 53
3.8.1 Erdôs-Rényi random graph.......................... 54
3.8.2 Configuration model............................... 57
3.8.3 Growing network with preferential attachment . . 59
3.9 Network motifs........................................... 61
3.10 Community detection ..................................... 62
3.10.1 Modularity........................................ 63
3.10.2 Markov stability.................................. 66
3.10.3 Infomap .......................................... 68
3.10.4 Overlapping communities........................... 71
4. Analysis of temporal networks 73
4.1 Definition............................................... 73
4.2 Temporal walks and paths................................. 76
4.2.1 Definition........................................ 76
4.2.2 Temporal distances................................ 78
4.2.3 Vector clock...................................... 82
4.3 Components............................................... 84
4.4 Temporal coherence of a triangle......................... 86
4.5 Centrality............................................... 88
4.5.1 Time-independent centrality....................... 89
4.5.2 Time-dependent centrality......................... 94
4.6 Statistical properties of event times.................... 99
4.6.1 Distribution of inter-event times................ 100
4.6.2 Coefficient of variation......................... 101
4.6.3 Local variation.................................. 102
4.6.4 Detrending....................................... 102
4.6.5 Fano factor...................................... 104
4.6.6 Detrended fluctuation analysis................... 107
4.7 Temporal correlation.................................... 109
Contents
xi
4.8 Null models and randomisation procedures ............... 114
4.9 Temporal motifs......................................... 115
4.10 Detection of change points and anomalies................ 119
4.11 Link prediction......................................... 122
4.12 Communities in temporal networks........................ 124
4.12.1 Modularity maximisation under estrangement
constraint ..................................... 126
4.12.2 Community matching approach..................... 127
4.12.3 Mapping change.................................. 129
4.12.4 Model-based approach ........................... 133
4.12.5 Multilayer modularity........................... 133
4.12.6 Tensor factorisation approach................... 137
5. Models of temporal networks 141
5.1 Models of non-Markovianity.............................. 141
5.2 Stochastic temporal networks............................ 142
5.3 Activity driven model................................... 143
5.4 Priority queue models................................... 148
5.5 Self-exciting processes................................. 154
5.5.1 Hawkes processes................................ 154
5.5.2 Cascading Poisson processes..................... 158
5.6 Markovian log-linear models............................. 161
5.7 Memory networks......................................... 164
5.8 Metapopulation model.................................... 170
6. Dynamics on temporal networks 175
6.1 Waiting-time paradox.................................... 176
6.2 Gillespie algorithms ................................... 179
6.3 Random walks ........................................... 185
6.3.1 Node-centric random walks....................... 185
6.3.2 Link-centric random walks....................... 189
6.4 Epidemic processes...................................... 191
6.4.1 Models of epidemic processes.................... 191
6.4.2 SIS dynamics on metapopulation models........... 195
6.4.3 SIR dynamics on the neighbour exchange network
model........................................... 197
6.4.4 Viral spreading dynamics under bursty
interaction..................................... 201
Xll
A Guide to Temporal Networks
6.4.5 SIR dynamics on a tree-like stochastic temporal
network.........................................207
6.5 Synchronisation..........................................208
Appendix A Discrete-time random walks on the line 213
Appendix B Transient and absorbing states of Markov chains 215
Appendix C Derivation of the degree distribution of the
Barabasi-Albert model 217
Bibli ography 219
Index 235
|
| any_adam_object | 1 |
| author | Masuda, Naoki 1976- Lambiotte, Renaud |
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| dewey-ones | 003 - Systems |
| dewey-raw | 003 |
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| dewey-sort | 13 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Book |
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| id | DE-604.BV043882021 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:37:35Z |
| institution | BVB |
| isbn | 9781786341143 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029291619 |
| oclc_num | 961903724 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-20 |
| owner_facet | DE-473 DE-BY-UBG DE-20 |
| physical | xii, 237 Seiten Illustrationen |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | World Scientific |
| record_format | marc |
| series | Series on complexity science |
| series2 | Series on complexity science |
| spelling | Masuda, Naoki 1976- Verfasser (DE-588)1093153784 aut A guide to temporal networks Naoki Masuda (University of Bristol, UK), Renaud Lambiotte (University of Namur, Berlgium) New Jersey World Scientific [2016] © 2016 xii, 237 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Series on complexity science vol. 4 Dynamik (DE-588)4013384-9 gnd rswk-swf Netzwerk (DE-588)4171529-9 gnd rswk-swf Netzwerk (DE-588)4171529-9 s Dynamik (DE-588)4013384-9 s DE-604 Lambiotte, Renaud Verfasser (DE-588)109957742X aut Series on complexity science vol. 4 (DE-604)BV039961107 4 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029291619&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Masuda, Naoki 1976- Lambiotte, Renaud A guide to temporal networks Series on complexity science Dynamik (DE-588)4013384-9 gnd Netzwerk (DE-588)4171529-9 gnd |
| subject_GND | (DE-588)4013384-9 (DE-588)4171529-9 |
| title | A guide to temporal networks |
| title_auth | A guide to temporal networks |
| title_exact_search | A guide to temporal networks |
| title_full | A guide to temporal networks Naoki Masuda (University of Bristol, UK), Renaud Lambiotte (University of Namur, Berlgium) |
| title_fullStr | A guide to temporal networks Naoki Masuda (University of Bristol, UK), Renaud Lambiotte (University of Namur, Berlgium) |
| title_full_unstemmed | A guide to temporal networks Naoki Masuda (University of Bristol, UK), Renaud Lambiotte (University of Namur, Berlgium) |
| title_short | A guide to temporal networks |
| title_sort | a guide to temporal networks |
| topic | Dynamik (DE-588)4013384-9 gnd Netzwerk (DE-588)4171529-9 gnd |
| topic_facet | Dynamik Netzwerk |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029291619&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV039961107 |
| work_keys_str_mv | AT masudanaoki aguidetotemporalnetworks AT lambiotterenaud aguidetotemporalnetworks |