Analysis of the Corporate Communication and Operational Value of the Chinese Epic Opera "The Long March" under the Perspective of Diversified Music

Abstract

In this study, a convolutional neural network is used to extract song label features in audio signals under a multivariate music perspective, and a traditional SIR model is improved to more accurately model information propagation. Music labels are normalized and factors such as node strength and edge weight differences are introduced to reflect the complex propagation process more accurately. In the enterprise propagation dynamics model, the multivariate music perspective is considered, and the practical application value of the model is increased by controlling the number of infected nodes in the neighbors of the state nodes. The parameter is increased from -1 to 1, which reduces the propagation critical value and actively promotes the information dissemination of the epic opera The Long March, providing a reference for the corporate communication strategy in the field of pluralistic music.