Overview
- First contributed volume on the theory of temporal networks
- Covers all trending theoretical topics
- Contributions gathered from the top international researchers in the field
Part of the book series: Computational Social Sciences (CSS)
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Table of contents (18 chapters)
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Front Matter
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Back Matter
Keywords
- time series analysis
- computational social science
- computational neuroscience
- big data and network theory
- time varying networks
- epidemic spreading processes
- network theory and modeling frameworks and tools
- measures of temporal network structure
- network theory and mesoscopic structures
- network theory and dynamic processes
- network epidemic spreading
- computational social sciences
- complexity
About this book
This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for the modeling of epidemics, optimization of transportation and logistics, as well as understanding biological phenomena.
Network theory has proven, over the past 20 years to be one of the most powerful tools for the study and analysis of complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the "big data" sets. This monograph will appeal to students, researchers and professionals alike interested in theory and temporal networks, a field that has grown tremendously over the last decade.
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Temporal Network Theory
Editors: Petter Holme, Jari Saramäki
Series Title: Computational Social Sciences
DOI: https://doi.org/10.1007/978-3-030-23495-9
Publisher: Springer Cham
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-23497-3Published: 13 November 2020
eBook ISBN: 978-3-030-23495-9Published: 29 October 2019
Series ISSN: 2509-9574
Series E-ISSN: 2509-9582
Edition Number: 1
Number of Pages: VIII, 375
Number of Illustrations: 16 b/w illustrations, 84 illustrations in colour
Topics: Applications of Graph Theory and Complex Networks, Computational Social Sciences, Complexity, Complex Systems