Research On Evaluation Of Copyright Value Of Movies Adapted From Network Literature

In recent years,the speed of the development of online novel’s IP has been amazing,and the channels for copyright operations have been continuously expanded.Internet novels have derived various forms such as movies with text content as the core.The entry of online literature into the film industry has become an unstoppable trend,and it will greatly contribute to the development of domestic films in the future.The flourishing prosperity of online literature will inevitably make domestic films become more and more multitudinous and superior in the future.Movies adapted from online literature are an important part of domestic films and have great potential for development.Researches on how to reasonably estimate the copyright value of movies adapted from online literature can effectively promote of the market of movies adapted from online literature’ progress and improvement.First,we construct a model for evaluating the copyright value of movies adapted from online literature based on the income method of three major methods about asset evaluation,and then we analyze the three important parameters in the income method model based on the specific status quo,the three important parameters are respectively the expected income of online literature adapted film copyrights,time of earnings and discount rate which should be selected reasonably.According to the development status of our country’s film industry,the main income of a film is from box office income.Because the derivatives market is relatively underdeveloped,this article only considers movie box office income in the research.As an important part of my country’s domestic films,the derivative income of films adapted from online literature is also negligible.Based on the regression of machine learning algorithms,this paper predicts the box office revenue of movies adapted from online literature,and selects 79non-animated movies adapted from online literature as samples which were released in China between 2000 in 2020.In the regression equation,the dependent variable is box office revenue,and the independent variables are eighteen influencing factors which were selected from the influencing factors of box office revenue about movies adapted from online literature.The training process was carried out by using the sklearn library with jupyter notebook.Through comparing of the corresponding evaluation indicators,it is found that the random forest regression is the most effective.Therefore,we use the random forest regression to predict the case’s box office revenue.In the part of case analysis,we firstly predict the example-"Lianqu 1980" ’s box office revenue through random forest regression which has the smallest error,and then make reasonable estimates of the remaining parameters,finally substitute all of them into the income method model to get its copyright value.This article mainly uses the income method to evaluate the copyright value of movies adapted from online literature,and uses multiple linear regression,random forest regression,XGBoost regression,support vector machine regression,and multiple regression algorithms to accurately estimate the box office revenue,thereby laying the foundation to precisie the assessment about the copyright value of movies adapting from online literature.At the end,we put forward the existing shortcomings and prospects for the future.This article is committed to making contributions to the development of the industry about network literature adaptation.