Network science has proved to be one of the most interesting research domain which has been adopted by many application domains. Eventually, after machine learning and soft computing techniques, researchers have shifted their attention to network science related areas. Network science is the dynamic analysis of graphical structure. Thus, the study of dynamics and structure of a network is referred as Network Science. Although there are many different fields in computer science, but computer and information research scientists have adopted network science as one of the most versatile computer science fields.
The idea behind introduction of Network Science domain is to study the dynamics of graphs. This is an extension to graph theory. Addition and removal of nodes and edges dynamically while analyzing streaming data leads to information retrieval.
Earlier, the areas of structure of different networks, be it any, like network of friend circle at facebook, twitter, and other social media websites; network of power system; network of connections among school friends; network of roads, railway lines, flights etc have many hidden patterns in them. Thus, to uncover these latent patterns, researchers have studied various metrics of these networks. Also, there are various technical terms like scale-free property, small-world property etc which can help in determining the theoretical behavior of networks. Moreover, information dissemination, spread of influential disease, broadcasting information and many other cascading systems have been explored using network science. Even marketing strategies and advertisement techniques have been studied using mathematical models of network science using SIS and SIR models. In addition to this, recently, researchers have been studying multi-layer networks, multiplex networks, and heterogeneous information networks for various application domains.
In a nutshell, network science has proved to be one of the most happening areas of research among many different fields in computer science. Also, the computer and information research scientists are keen to learn, implement and explore more about this domain. The prior knowledge of graph theory, statistics and probability is very important to click this domain. Although, there are different fields in computer science which have seek attention of academic researchers and industrialists, but network science has gained much potential in recent years.