Improved structural algorithm for uncovering community structure in networks

The discovery of underlying community structures is a common challenge in the analysis of network data. This paper presents a novel algorithm which gives consideration to both modularity and robustness of the clustering. It´s based on SCAN which can detect more details about clusters, hubs and outliers. In order to demonstrate the advantages of this new algorithm in coordinating networks scale with the same similarity, an evaluation is implemented by the classical karate datasets at the end of the paper.