Chinese contemporary music has made tremendous progress in the twentieth century. After entering the twentieth century, with the rise of pop music, Chinese contemporary music has gradually been forgotten by people. Apparently, Chinese contemporary music has a long history and covers huge varieties. Nevertheless, the diffusion of Chinese contemporary music is restricted by many factors. The fundamental reason is that people’s cognition of Chinese contemporary music has changed. However, the rise of social networks provides a new opportunity for the diffusion of Chinese contemporary music. By searching nodes with high influence in social networks, where the node is enabled by the sensor, we transform the problem for maximizing public opinion into a process of searching nodes set of maximum influence, thus providing power for the diffusion of Chinese contemporary music. In this paper, from the perspective of percolation, the network connectivity changes caused by node failure are considered, and the set selection problems of high-influence individuals are mapped to the optimal percolation problem when the network has a percolation transition. Then an influence maximization algorithm is proposed based on the network percolation process, and the efficiency of the proposed algorithm is optimized. Through experiments, we can infer the reasonable range of maximum searching times for the influence maximization algorithm. Meanwhile, compared with other baselines, the searching time of the algorithm proposed in this paper is also the least. The experimental results reveal that the proposed algorithm is feasible to diffuse Chinese contemporary music and maximize its public opinion and has a strong impetus for the revival of Chinese contemporary music.