An Efficient Two Stage Clustering Algorithm for Signed Social Networks

Abstract

In this paper, a clustering algorithm named ICRA, which is based on Breadth first search approach has proposed. In this algorithm a new robust criterion NCN has introduced for deciding which vertex processing first from the list of vertices which are not present in any cluster. It efficiently mines the ordered sequences and update as well. This work is useful in community mining in social network analysis. The proposed algorithm is inspired by CRA algorithm, which does clustering twice. The proposed approach suits signed social networks too, and effectively mine negative vertices. In addition, this algorithm improves the predictive performance; especially for negative linked inter-communities datasets hence increases the accuracy when tested with the Gahuku - Gama dataset.