LEVERAGING BIG DATA FOR CRITICAL THINKING AND INNOVATION IN CHINESE WEB DRAMAS TO SATISFY AUDIENCES

Abstract

The phenomenon of web drama in China has become increasingly popular; this is a good time to establish a stronger substance and satisfy the public with the help of the big data context. This work relates to the general usage of big data to improve the areas of interest and to develop a program for predicting what people are most interested in watching and creating new shows based on the results of the analysis. To the writers and directors, big data holds significant potential to enrich the storylines, the characters, and the portrayals. To which end, these critical reviewers can obtain more detailed analysis from empirical data for criticism. The researchers used AMOS 24 and Bootstrap estimator to simulate the study, and they recruited 365 participants; the involved groups were the viewers, the directors, the scriptwriters, and the reviewers. In this context, the purpose of the study is to identify to what extent and how big data modifies creative and decision influences associated with Chinese Web Dramas to enhance information processing, creativity, and viewership