Network Science

摘要

This chapter reviews the highly interdisciplinary field of network science, which is concerned with the study of networks, be they biological, technological, or scholarly in character. It contrasts, compares, and integrates techniques and algorithms developed in disciplines as diverse as mathematics, statistics, physics, social network analysis, information science, and computer science. A coherent theoretical framework, including static and dynamical modeling approaches, is provided along with discussion of non-equilibrium techniques recently introduced for modeling growing networks. The chapter also provides a practical framework by reviewing major processes involved in the study of networks such as network sampling, measurement, modeling, validation, and visualization. For each of these processes, we explain and exemplify commonly used approaches. Aiming at a gentle yet formally correct introduction of network science theory, we explain terminology and formalisms in considerable detail. Although the theories come from a mathematical, formulae-laden world, they are highly relevant for the effective design of technological networks, scholarly networks, communication networks, and so on. We conclude with a discussion of promising avenues for future research.