Abstract Detecting influential nodes is still a popular issue in social networks and many excellent detecting methods have been put forward. However, most of them aim to improve the accuracy and efficiency of the algorithm, but ignore invulnerability of networks. Based on essential factors of influence propagation (such as the location and neighborhood of source node, propagation rate) and network invulnerability, we propose a novel strategy to search the influential nodes in terms of the local topology and the global location. Two important indicators are node diffusion degree and node cohesion degree, which are used to increase the probability of influence diffusion and reduce the feasibility of network collapse. More specially, the loss of global efficiency and the loss of local efficiency are applied to evaluate the impact of the algorithm from the perspective of network invulnerability. The experimental results in the real networks show that our method achieves an excellent balance between detecting accuracy and network invulnerability. The detected influential nodes are the ones that have great influence and can resist certain damage and disturbance of the networks.

中文翻译：

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基于网络无懈可击的社交网络影响节点检测

摘要 检测有影响力的节点仍然是社交网络中的一个热门问题，已经提出了许多优秀的检测方法。然而，他们中的大多数旨在提高算法的准确性和效率，而忽略了网络的无懈可击。基于影响传播的基本因素（如源节点的位置和邻域、传播速率）和网络的无懈可击，我们提出了一种新的策略来根据局部拓扑和全局位置搜索有影响的节点。两个重要的指标是节点扩散度和节点凝聚度，用于增加影响扩散的概率，降低网络崩溃的可行性。更特别的是，应用全局效率损失和局部效率损失，从网络无懈可击的角度评价算法的影响。在真实网络中的实验结果表明，我们的方法在检测准确度和网络无懈可击之间取得了很好的平衡。检测到的有影响的节点是具有较大影响力并且能够抵抗网络一定破坏和扰动的节点。