Social Network Analysis Using Community Detection Algorithm

Abstract

As we know that data in real world is growing at a very fast pace. So it is very difficult to make analysis on this data which can be represented in the form of network. So to ease the computation or analysis of the complex network we divide the complete network into various communities on the basis of characteristics (i.e. distance between the nodes, modularity of sub graph). In this project I have studied three different algorithms for community detection in a network. These algorithms are based on the idea of optimizing a modularity function. The idea of detecting communities by optimizing a modularity function was proposed by Newman. First one is Louvain algorithm second one is extension of Louvain algorithm with a so called multilevel refinement procedure and last one is smart local moving (SLM) algorithm. For large size network SLM algorithm is preferred over other two algorithms