Parallel Community Mining in Social Network using Map-reduce

Abstract

The mobile social network plays an essential role as the spread of information and relationship. This paper proposes a parallel algorithm based on MapReduce for finding community in a mobile social network where individuals communicate with one another using mobile phones with register identification information and analyzes the behavior of the communication patterns with taking the actual call detail records received and dialed by users into account. The proposal algorithm is composed of three main components map, reduce and merge for mining groups and a dynamic programming algorithm for selecting subgroups to combine into a big community. Empirical studies on a large real-world mobile social network show that performance of our algorithm is an effective and fast algorithm for mining community in social network.