Table of contents
About this book
This book provides an overview of network science from the perspective of diverse academic fields, offering insights into the various research areas within network science. The authoritative contributions on statistical network analysis, mathematical network science, genetic networks, Bayesian networks, network visualisation, and systemic risk in networks explore the main questions in the respective fields: What has been achieved to date? What are the research challenges and obstacles? What are the possible interconnections with other fields? And how can cross-fertilization between these fields be promoted?
Network Science comprises numerous scientific disciplines, including computer science, economics, mathematics, statistics, social sciences, bioinformatics, and medicine, among many others. These diverse research areas require and use different data-analytic and numerical methods as well as different theoretical approaches. Nevertheless, they all examine and describe interdependencies, associations, and relationships of entities in different kinds of networks.
The book is intended for researchers as well as interested readers working in network science who want to learn more about the field – beyond their own research or work niche. Presenting network science from different perspectives without going into too much technical detail, it allows readers to gain an overview without having to be a specialist in any or all of these disciplines.
Editors and affiliations
- Book Title Network Science
- Book Subtitle An Aerial View
- DOI https://doi.org/10.1007/978-3-030-26814-5
- Copyright Information Springer Nature Switzerland AG 2019
- Publisher Name Springer, Cham
- eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
- Hardcover ISBN 978-3-030-26813-8
- Softcover ISBN 978-3-030-26816-9
- eBook ISBN 978-3-030-26814-5
- Edition Number 1
- Number of Pages IX, 119
- Number of Illustrations 21 b/w illustrations, 16 illustrations in colour
Statistical Theory and Methods
Probability Theory and Stochastic Processes
Probability and Statistics in Computer Science
Computer Appl. in Social and Behavioral Sciences
Statistics for Life Sciences, Medicine, Health Sciences
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