Community detection using ant colony optimization techniques

Parallel to the continuous growth of the Internet, which allows people to share and collaborate more, social networks have become more attractive as a research topic in many different disciplines. Community structures are established upon interactions between people. Detection of these communities has become a popular topic in computer science. Currently, community detection is commonly performed using Social Network Analysis (SNA) algorithms based on clustering. The main disadvantage of these methods is their high computational costs and non-scalability on large-scale social networks. Our main aim is to reduce these computational costs without loss on solution quality. In this study, we focus on Ant Colony Optimization techniques to find cliques in the network and assign these cliques as nodes in a reduced graph to use with SNA algorithms.