Название: Network Science: An Aerial View Автор: Francesca Biagini, Goran Kauermann
Издательство: Springer
Год: 2020
Страниц: 124
Язык: английский
Формат: pdf (true), epub
Размер: 14.3 MB
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 is a term used for a wide field of methods all related to analyzing networks and/or network data. This ranges from mathematical questions to applied data analytic problems. We give a general overview of the different aspects and refer to the chapters in this book. Network science, the science of analyzing networks, has become increasingly important. A network is a collection of actors (nodes), which are connected with each other (through edges). Examples include genetic, social, and traffic networks, to name but a few. Research questions are, among others, the dynamic behavior of the network, the transmission of information through the network, or the network structure itself. Networks are simple in structure and in principle one can even represent the network as squared matrix, so that edges are numbers in the matrix. A friendship network can for instance be written as matrix with entries 1 (for an existing edge) and 0 (otherwise). And while the structure of a network is simple, its analysis and modeling can get rather complex. Moreover, if a network gets large, the behavior in the network follows asymptotic rules, whose derivation is challenging. These aspects become apparent with the increasing availability of network data. Today, we live in a data-driven society in which information is measured, recorded, and stored in many areas of daily life, and network data, available in nearly all of these areas, need to be analyzed.
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.
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