A Quantitative Evaluation Method for Communication Impact of Sporting Events Based on SIR Dynamic Diffusion Model

Abstract

The quantitative evaluation for communicable events has been a significant demand in digital society management. This paper takes the 2022 Winter Olympic Games as the object and proposes a quantitative evaluation method for the communication impact of sporting events based on the SIR dynamic diffusion model. Specifically, this study combinesa long short-term memory (LSTM) neural network, wavelet packet decomposition, and other techniques to propose a digital evaluation approach for the quantification of communication impact. Among these, the transfer probability is quantified and calculated by the user node reputation value algorithm. In the experimental simulation, the effects of different mechanisms of joining consensus nodes and blockchain on the propagation probability in the model are discussed, respectively. Some simulation experiments are conducted on the real-world scenes of social networks, and the simulation results show that the number of nodes spreading false information is reduced by 9.89% compared with baseline methods. Finally, a sports event communication effect evaluation index system was constructed, and the data characteristics of indicators at all levels were analyzed to preliminarily predict the communication effect, after which the fuzzy hierarchical comprehensive evaluation method, combined with the expert survey method, was used to empirically evaluate, and test the communication effect of its events.