Network Science deals with models, methods, tools, and mathematical techniques to study and analyze the behaviour of networks.
Networks comprise entities represented as nodes (also referred to as vertices), and the relationships among the nodes are denoted by edges (also referred to links).
Networks are everywhere – connecting ‘agents’ of different types by edges representing their interactions: phone networks connect people through voice, text, or video linkages; electrical networks capture the connectivity between sources of generation and loads which consume the power that flows in the network; biological networks are used to model the nature of interaction between agents representing biological entities such as proteins; social networks model online interactions between social agents – people; and so on.
Network Science today has rapidly emerged as a vast interdisciplinary field of investigation, with tools and techniques drawn from many disciplines, ranging from the basic sciences, such as physics and biology, to the engineering sciences such as electrical engineering, through graph theory and learning in computer science and mathematics, and the social sciences, drawing in topics from microeconomics and game theory.
One of the central goals of Network Science is the study of complex phenomena arising from the interaction of a large number of agents interconnected by a network of linkages. These studies attempt to model and characterize the behaviour of agents located at the nodes, the impact of network structure on such behaviour and their characterization, and the dynamics that may result from changes to the network structure and properties.