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Network Science is the emerging field concerned with the study of
large, realistic networks. This interdisciplinary endeavor,
focusing on the patterns of interactions that arise between
individual components of natural and engineered systems, has been
applied to data sets from activities as diverse as high-throughput
biological experiments, online trading information, smart-meter
utility supplies, and pervasive telecommunications and surveillance
technologies. This unique text/reference provides a fascinating
insight into the state of the art in network science, highlighting
the commonality across very different areas of application and the
ways in which each area can be advanced by injecting ideas and
techniques from another. The book includes contributions from an
international selection of experts, providing viewpoints from a
broad range of disciplines. It emphasizes networks that arise in
nature-such as food webs, protein interactions, gene expression,
and neural connections-and in technology-such as finance, airline
transport, urban development and global trade. Topics and Features:
begins with a clear overview chapter to introduce this
interdisciplinary field; discusses the classic network science of
fixed connectivity structures, including empirical studies,
mathematical models and computational algorithms; examines
time-dependent processes that take place over networks, covering
topics such as synchronisation, and message passing algorithms;
investigates time-evolving networks, such as the World Wide Web and
shifts in topological properties (connectivity, spectrum,
percolation); explores applications of complex networks in the
physical and engineering sciences, looking ahead to new
developments in the field. Researchers and professionals from
disciplines as varied as computer science, mathematics,
engineering, physics, chemistry, biology, ecology, neuroscience,
epidemiology, and the social sciences will all benefit from this
topical and broad overview of current activities and grand
challenges in the unfolding field of network science.
Network Science is the emerging field concerned with the study of
large, realistic networks. This interdisciplinary endeavor,
focusing on the patterns of interactions that arise between
individual components of natural and engineered systems, has been
applied to data sets from activities as diverse as high-throughput
biological experiments, online trading information, smart-meter
utility supplies, and pervasive telecommunications and surveillance
technologies. This unique text/reference provides a fascinating
insight into the state of the art in network science, highlighting
the commonality across very different areas of application and the
ways in which each area can be advanced by injecting ideas and
techniques from another. The book includes contributions from an
international selection of experts, providing viewpoints from a
broad range of disciplines. It emphasizes networks that arise in
nature-such as food webs, protein interactions, gene expression,
and neural connections-and in technology-such as finance, airline
transport, urban development and global trade. Topics and Features:
begins with a clear overview chapter to introduce this
interdisciplinary field; discusses the classic network science of
fixed connectivity structures, including empirical studies,
mathematical models and computational algorithms; examines
time-dependent processes that take place over networks, covering
topics such as synchronisation, and message passing algorithms;
investigates time-evolving networks, such as the World Wide Web and
shifts in topological properties (connectivity, spectrum,
percolation); explores applications of complex networks in the
physical and engineering sciences, looking ahead to new
developments in the field. Researchers and professionals from
disciplines as varied as computer science, mathematics,
engineering, physics, chemistry, biology, ecology, neuroscience,
epidemiology, and the social sciences will all benefit from this
topical and broad overview of current activities and grand
challenges in the unfolding field of network science.
The study of network theory is a highly interdisciplinary field,
which has emerged as a major topic of interest in various
disciplines ranging from physics and mathematics, to biology and
sociology. This book promotes the diverse nature of the study of
complex networks by balancing the needs of students from very
different backgrounds. It references the most commonly used
concepts in network theory, provides examples of their applications
in solving practical problems, and clear indications on how to
analyse their results. In the first part of the book, students and
researchers will discover the quantitative and analytical tools
necessary to work with complex networks, including the most basic
concepts in network and graph theory, linear and matrix algebra, as
well as the physical concepts most frequently used for studying
networks. They will also find instruction on some key skills such
as how to proof analytic results and how to manipulate empirical
network data. The bulk of the text is focused on instructing
readers on the most useful tools for modern practitioners of
network theory. These include degree distributions, random
networks, network fragments, centrality measures, clusters and
communities, communicability, and local and global properties of
networks. The combination of theory, example and method that are
presented in this text, should ready the student to conduct their
own analysis of networks with confidence and allow teachers to
select appropriate examples and problems to teach this subject in
the classroom.
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