With the rapid development of social networks, it has become extremely important to evaluate the propagation capabilities of the nodes in a network. Related research has wide applications, such as in network monitoring and rumor control. However, the current research on the propagation ability of network nodes is mostly based on the analysis of the degree of nodes. The method is simple, but the effectiveness needs to be improved. Based on this problem, this paper proposes a method that is based on Tsallis entropy to detect the propagation ability of network nodes. This method comprehensively considers the relationship between a node’s Tsallis entropy and its neighbors, employs the Tsallis entropy method to construct the TsallisRank algorithm, and uses the SIR (Susceptible, Infectious, Recovered) model for verifying the correctness of the algorithm. The experimental results show that, in a real network, this method can effectively and accurately evaluate the propagation ability of network nodes.

中文翻译：

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基于Tsallis熵的复杂网络影响节点排序新方法


随着社交网络的快速发展，评估网络中节点的传播能力变得极其重要。相关研究在网络监控、谣言控制等方面有着广泛的应用。然而，目前对网络节点传播能力的研究大多基于节点度的分析。方法简单，但效果有待提高。针对这一问题，本文提出一种基于Tsallis熵的网络节点传播能力检测方法。该方法综合考虑节点Tsallis熵与其邻居节点的关系，采用Tsallis熵方法构建TsallisRank算法，并利用SIR（Susceptible、Infectious、Recovered）模型验证算法的正确性。实验结果表明，在实际网络中，该方法能够有效、准确地评估网络节点的传播能力。