Finding key nodes on terrorist networks through k-shell based on structural hole

Terrorist attacks do great harm to the economic and social development. Structural perspective provides an explanatory framework for the activities of terrorist organizations which are social network structure. Network centrality are used to to identify key nodes in terrorist organizations. Existing researches often neglect the optimization of centrality indicators by structural holes. By considering structural holes that local factors impact on the overall network. We propose an k-shell based on structural hole method to find key nodes. We conducted experiments on three open source data sets of terrorist organization networks. Compare with the traditional centrality index to prove the effectiveness and accuracy of the algorithm proposed in this paper. The results show that, with the proximity of the center algorithm of the center compared to the number of dielectric, eigenvector centrality, hollow structure and algorithms k-shell value algorithm, the better the improvement in recognition accuracy and discrimination results. The algorithm can be used to identify key nodes in terrorist organizations and provide feasible methods for analyzing and combating terrorist organizations.