The core nodes identification method through adjustable network topology information

Abstract

A social network has an in-born core-fringe structure. To increase the core nodes resolution, the paper proposes a new method, named KSCNR (K-Shell and Salton index based core node recognition) method, that combines both the local network topology features (Salton index with gravitational centrality) and the global network topology features (K-Shell iteration) to identify core nodes. The KSCNR method utilizes the weights to adjust the influences of the local and the global topology features according to the core nodes preferences, which makes the KSCNR method suitable for different social network scenarios. The experimental results show that the KSCNR method outperforms the known methods such as the K-Shell, the BC, the DC and the CC methods in the light of both effectiveness and accuracy.