Research On The Payment Model Of Caixin Digital News

Today,with the rapid and comprehensive development of the Internet,the digital content of the media,relying on the era background of the development of the Internet,is gradually going to the mainstream.Various media at home and abroad began to implement the payment model for digital content,which attracted attention and discussion from all walks of life.However,the current domestic research on the digital content payment mode mainly focuses on the development trend of the payment mode,or on the introduction of the existing digital content payment mode media,there is a lack of detailed research on the payment mode.From the perspective of the overall development trend of digital content payment in domestic media,and taking the introduction of paid news by Caixin Media on the whole platform since October 2017 as an example,this paper analyses the implementation and development,characteristics,structure and development strategy of digital content payment mode in Caixin News,studies the specific payment mode of Caixin News,analyses the advantages and disadvantages of its paid news development,and conducts comprehensive research.The future development direction of digital content in domestic media will provide development thinking and suggestions for the payment model of digital content in domestic media.This paper analyses the characteristics and structure of the digital content payment model of Caixin News from different aspects,that is,the development of Caixin Digital News and the formation of the payment model,and the connotation and characteristics of Caixin Digital News.Caixin News Digital Content Payment Model has been implemented on the whole platform since October,2017.Although it has not been implemented for a long time so far,it can be found that there are some shortcomings in the process of Caixin News Digital Content Payment,which need further optimization,through the analysis of the existing problems,and then combined with the existing problems.Suggestions for optimization are put forward.