%0 Journal Article
%T Clustering online social network communities using genetic algorithms
%A Mustafa H. Hajeer
%A Alka Singh
%A Dipankar Dasgupta
%A Sugata Sanyal
%J Computer Science
%D 2013
%I arXiv
%X To analyze the activities in an Online Social network (OSN), we introduce the concept of "Node of Attraction" (NoA) which represents the most active node in a network community. This NoA is identified as the origin/initiator of a post/communication which attracted other nodes and formed a cluster at any point in time. In this research, a genetic algorithm (GA) is used as a data mining method where the main objective is to determine clusters of network communities in a given OSN dataset. This approach is efficient in handling different type of discussion topics in our studied OSN - comments, emails, chat expressions, etc. and can form clusters according to one or more topics. We believe that this work can be useful in finding the source for spread of this GA-based clustering of online interactions and reports some results of experiments with real-world data and demonstrates the performance of proposed approach.
%U http://arxiv.org/abs/1312.2237v1