Research on Early Warning Model of Wushu Event Broadcasting Right Operation Risk Based on Big Data XGBoost Algorithm

Abstract

Abstract Under the background of the development of new media technology, the attention of wushu events in the society is gradually increasing, which makes the competition in the event broadcasting market more and more intense. This paper focuses on the problem of predicting the operational risk of wushu event broadcasting rights, based on the GBRT algorithm, innovatively improves the traditional loss function, introduces the regular term, and proposes the application of XGBoost algorithm in the operational risk prediction of wushu event broadcasting rights. The improved algorithm divides the operational risk of broadcasting rights into two main levels, covering three primary and 10 secondary indicators. In this study, the XGBoost algorithm is applied in the early warning of informing proper operation risk, which is classified into two main levels, covering 3 primary and 10 secondary indicators. The article also conducts an in-depth experimental analysis of the risk of overpremium of the event rights and the risk of matching the audience’s demand. In addition, according to the results of audience analysis, men have become the primary audience of wushu events, with a frequency of up to 401 times. Based on the XGBoost algorithm, the wushu event broadcasting right operation risk warning system can effectively predict and help the event broadcasting platform to avoid the potential operation risk, which provides valuable data support for the market decision-making.