Abstract
In the spread of information, a small fraction of nodes play an important role in the dynamics; therefore, detecting these influential nodes helps control the spread of information. However, classical methods can choose a single influential node yet fail in the case of multiple influential nodes. In this paper, we analyze the collective influence and overlapping influence of multiple spreaders. Further, based on the overlapping influence between spreaders, we clarify the problem of why multiple influential spreaders may have a low collective influence. Finally, a new algorithm is proposed to choose multiple spreaders, and the performance of the algorithm is validated on real networks.
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