Legal Risk Prediction and Prevention and Control of Sports Event Rebroadcasting in the Internet Age

Abstract

Due to the inadequacy of broadcasting right, information network transmission right, and rebroadcasting right, the number of infringing rebroadcasts of sporting events is rising. Combined with sophisticated mathematical analysis techniques, the research literature on the legal risk prediction of sports event rebroadcasting in the Internet era is scarce. This study examines the legal risk prognosis, prevention, and management of sports event rebroadcasting in the Internet era. The feature variable set of the sample set is subjected to feature filtering, reducing the prediction model's complexity. Stacking is used to integrate the LightGBM and Logistic regression models, and the Logistic regression legal risk prediction procedure is described. Based on LightGBM, this study predicts the legal hazards associated with Internet rebroadcasting of sporting events. Moreover, these research results validate the model's efficacy.