Ranking importance in nodes is a commonly used analysis method for identifying key nodes in complex networks, and importance of analyzing nodes in the network is a great help to a deeper understanding network characteristics. In order to further improve the accuracy of node evaluation based on existing methods, this paper introduces the concept of Binomial Entropy to quantify the importance of nodes in the network, measures the mutual influence between nodes through neighborhood similarity, and simultaneously uses Van der Waals force to abstract the interaction between nodes. Therefore, a key node identification method based on binomial entropy and Van der Waals force between neighboring nodes is proposed. This method is a comprehensive consideration of the local and global characteristics of nodes from the overall information flow of the network and the location and interaction relationship between adjacent nodes, and a selection from three similar algorithms to verify the performance through three evaluation indicators. The experimental results show that the algorithm in this paper is good in performance in judging important nodes.