Abstract: Accurately measuring the importance of nodes in a complex network helps to study the resistance to destruction and robustness of the network. To compensate for the limitations of existing algorithms in assessing one-sided perspectives, this paper introduces Van der Waals Force into complex networks. It maps the nodes in the network as molecules or atoms, and represents the degree of nodes as Van der Waals constants of molecules or atoms. It defines the influence of nodes in terms of Van der Waals Force, takes into account the percentage of path information between nodes, and proposes a Van der Waals Force-based important node mining algorithm called VDWF (Van der Waals Force). This algorithm considers both the local information of the network and the global topology. To verify the effectiveness and applicability of the algorithm, monotonicity index, network efficiency, and great connectivity coefficient are used as evaluation indices. Six real data sets from different domains are selected for control experiments with other algorithms. The results show that the Van der Waals Force algorithm can more effectively mine important nodes in complex networks and accurately distinguish the differences in the importance of different nodes.