Research on the Evaluation of Program Influence Based on PageRank Algorithm

The paper introduces the complex network theory into the program influence evaluation system. We collect relevant data of the variety shows on Tencent Video Platform from 2016-2021 and establish the program comprehensive influence algorithm program. The comprehensive influence consists of two direct and indirect parts, the direct influence is calculated from the total view counts, the comments in the latest issue, and the fans of the official program account. The indirect influence is calculated by PageRank, LeaderRank and TimedPageRank through the program page. The results obtained by the algorithm shows that the output of highly influential variety shows has increased in recent years. Even though COVID-19 in 2020 reduced the total production of variety shows, it still produces a relatively high proportion of influential programs. High influence programs are mainly “Develop” and “Game” programs, “Cultural” programs rank low. Inspire our need to strengthen the content production and value concept guidance of the variety show market, and deepen the content innovation and reform of the “Cultural” programs themselves.