An identification method for important nodes based on k-shell and structural hole

Identifying important nodes that have great influence on propagation in social networks has an important significance on understanding and controlling spread of information in the network. On the basis of the idea that location of nodes can affect their ability to communicate, it is pointed out that the important nodes in networks consisted by two kinds of nodes, namely opinion leaders and structural holes. But most of the existing methods for identifying important nodes does not take the structural holes into account. This article proposes a hybrid important nodes identification algorithm, which combines k-shell and network effective size, aiming at finding a group of nodes that are the most central and bridging. Doing experiments on five actual data sets based on susceptible–infected–removed propagation model, the experimental results show that, comparing with algorithms on the basis of degree, closeness, k-shell, between-ness and network effective size, the proposed algorithm has the highest identification accuracy.