基于标签传播识别网络中的关键节点

基于标签传播动力学提出了一种识别网络关键节点的算法,主要思想是把每个节点接收到不同标签的数量作为判断节点重要性的指标。应用两种不同的传播模型,在不同网络上与其它中心性指标作比较。结果表明:基于标签传播的中心性指标比其它的中心性方法可以更好地识别网络中的关键节点。基于标签传播的中心性指标还具有以下优势:不需要利用网络的结构信息,因此可以推广到大规模网络上;揭示了一种现象——好的接收者往往也是好的传播者。

Identifying Influential Nodes in Complex Networks Based on the Label Spreading Dynamics

In this paper, based on the label spreading dynamics, we propose a centrality index to identify influential nodes in complex networks, where the influence of a node is measured by how many different labels who have received.Under different spreading models, we compare our index with several traditional centrality indices in different networks, our results indicate that the performance of our index is better than others.Moreover, there are two typical advantages: 1), our algorithm does not use the structure information of networks, so which can be generalized to large-scale networks;2), our algorithm implies a conclusion-a good receiver is also a good spreader.