Detection of Communities in Large Scale Networks

With the advent of the internet and the boom of information sharing, study of networks has begun to play a central role in social science, mathematics and statistical analysis. A large variety of data can be modeled via complex networks making them increasingly more important for research. However, it is not easy to extract meaningful information from a mesh of interconnected of nodes.. That is why, detection of communities in network has become of utmost importance in recent times. Communities can be said to act as meta-nods. They correspond to functional units of the system and hence, often shed light on the function of the system represented by the network. Detecting an underlying community structure in a network thus allows us to create a map of a network which makes it easier to study. In this paper, we examine a number of research involving detection of communities and summarise them based on their avenues of approach to solving the problem.