Research on Influence Ranking of Chinese Movie Heterogeneous Network Based on PageRank Algorithm

Abstract

As the Chinese film industry flourishes, it is of great significance to assess the influence of film and film participants. Based on the theory of complex networks, this paper studies the ranking of influence in the film-participant heterogeneous network. Participants may have multiple identities such as directors, screenwriters, and actors. Referring to the PageRank algorithm of the page ranking algorithm and combining the features of the film industry, a new ranking algorithm, MovieRank, is proposed. The core three rules are as follows: (1) If the movie rank is high, the ranking of the participating players is also high; and if the participants have a high ranking. It also has a high ranking in participating movies; (2) the rankings of films and participating players are influenced by their social attributes; (3) the movie contributes more to their high-position participants, and the participants contribute more to the movie that they play an important role in it. Experimenting with Chinese movie information as experimental data, it is found that the new algorithm MovieRank actually performs better than the original PageRank algorithm. At the same time, through the analysis of the experimental results, it is found that the cooperation between actors from Hong Kong and Taiwanese is very close in the Chinese movie network, and that the directors and screenwriters have higher stability and less change than the actors.