TV Series Ratings Analysis and Prediction Based on Decision Tree

Abstract

In the new era of the rapid development of the film and television industry, audience rating, as an important indicator for evaluating film and television works, and an important reference for program production, arrangement, adjustment, plays a significant role in the film and television industry. Therefore, it is necessary to predict the audience rating of TV series to assist the production and arrangement of TV series. This paper selects relevant information about popular TV series in 2019 to analyze the influences of six factors, including broadcast time period, score on Douban.com, main actors, directors, and broadcasting platform, on TV series ratings through two different decision tree models. On this basis, this paper compares the experimental results of the two models through many experiments, and chooses ID3 decision tree algorithm as the prediction model of TV series ratings. The results show that the prediction model constructed in this paper has a good effect, and the accuracy rate can reach 84.05%, which can be used to predict TV series audience rating.